bw 362

BW362SAP NetWeaver BW, powered by

SAP HANASAP NetWeaver - Business Intelligence

Date

Training Center

Instructors

Education Website

Instructor HandbookCourse Version: 98Course Duration: 3 Day(s)Material Number: 50116138Owner:

An SAP Compass course - use it to learn, reference it for work

For Any SAP / IBM / Oracle - Materials Purchase Visit : www.sapcertified.com OR Contact Via Email Directly At : [email protected]


SAP HANA Training Email: [email protected] www.araniconsulting.com


Copyright

Copyright © 2013 SAP AG or an SAP affiliate company. All rights reserved.

No part of this publication may be reproduced or transmitted in any form or for any purposewithout the express permission of SAP AG. The information contained herein may be changedwithout prior notice.

Some software products marketed by SAP AG and its distributors contain proprietary softwarecomponents of other software vendors.

Trademarks

Adobe, the Adobe logo, Acrobat, PostScript, and Reader are trademarks or registered trademarks ofAdobe Systems Incorporated in the United States and other countries.

Apple, App Store, FaceTime, iBooks, iPad, iPhone, iPhoto, iPod, iTunes, Multi-Touch, Objective-C,Retina, Safari, Siri, and Xcode are trademarks or registered trademarks of Apple Inc.

Bluetooth is a registered trademark of Bluetooth SIG Inc.

Citrix, ICA, Program Neighborhood, MetaFrame now XenApp, WinFrame, VideoFrame, andMultiWin are trademarks or registered trademarks of Citrix Systems Inc.

Computop is a registered trademark of Computop Wirtschaftsinformatik GmbH.

Edgar Online is a registered trademark of EDGAR Online Inc., an R.R. Donnelley & Sons Company.

Facebook, the Facebook and F logo, FB, Face, Poke, Wall, and 32665 are trademarks of Facebook.

Google App Engine, Google Apps, Google Checkout, Google Data API, Google Maps, GoogleMobile Ads, Google Mobile Updater, Google Mobile, Google Store, Google Sync, Google Updater,Google Voice, Google Mail, Gmail, YouTube, Dalvik, and Android are trademarks or registeredtrademarks of Google Inc.

HP is a registered trademark of the Hewlett-Packard Development Company L.P.

HTML, XML, XHTML, and W3C are trademarks, registered trademarks, or claimed as genericterms by the Massachusetts Institute of Technology (MIT), European Research Consortium forInformatics and Mathematics (ERCIM), or Keio University.

IBM, DB2, DB2 Universal Database, System i, System i5, System p, System p5, System x, Systemz, System z10, z10, z/VM, z/OS, OS/390, zEnterprise, PowerVM, Power Architecture, PowerSystems, POWER7, POWER6+, POWER6, POWER, PowerHA, pureScale, PowerPC, BladeCenter,System Storage, Storwize, XIV, GPFS, HACMP, RETAIN, DB2 Connect, RACF, Redbooks,OS/2, AIX, Intelligent Miner, WebSphere, Tivoli, Informix, and Smarter Planet are trademarksor registered trademarks of IBM Corporation.

Microsoft, Windows, Excel, Outlook, PowerPoint, Silverlight, and Visual Studio are registeredtrademarks of Microsoft Corporation.

INTERMEC is a registered trademark of Intermec Technologies Corporation.

IOS is a registered trademark of Cisco Systems Inc.

The Klout name and logos are trademarks of Klout Inc.

Linux is the registered trademark of Linus Torvalds in the United States and other countries.

Motorola is a registered trademark of Motorola Trademark Holdings LLC.

Mozilla and Firefox and their logos are registered trademarks of the Mozilla Foundation.

Novell and SUSE Linux Enterprise Server are registered trademarks of Novell Inc.

g201311103942





OpenText is a registered trademark of OpenText Corporation.

Oracle and Java are registered trademarks of Oracle and its affiliates.

QR Code is a registered trademark of Denso Wave Incorporated.

RIM, BlackBerry, BBM, BlackBerry Curve, BlackBerry Bold, BlackBerry Pearl, BlackBerry Torch,BlackBerry Storm, BlackBerry Storm2, BlackBerry PlayBook, and BlackBerry AppWorld aretrademarks or registered trademarks of Research in Motion Limited.

SAVO is a registered trademark of The Savo Group Ltd.

The Skype name is a trademark of Skype or related entities.

Twitter and Tweet are trademarks or registered trademarks of Twitter.

UNIX, X/Open, OSF/1, and Motif are registered trademarks of the Open Group.

Wi-Fi is a registered trademark of Wi-Fi Alliance.

SAP, R/3, ABAP, BAPI, SAP NetWeaver, Duet, PartnerEdge, ByDesign, SAP BusinessObjectsExplorer, StreamWork, SAP HANA, the Business Objects logo, BusinessObjects, Crystal Reports,Crystal Decisions, Web Intelligence, Xcelsius, Sybase, Adaptive Server, Adaptive Server Enterprise,iAnywhere, Sybase 365, SQL Anywhere, Crossgate, B2B 360° and B2B 360° Services, m@gicEDDY, Ariba, the Ariba logo, Quadrem, b-process, Ariba Discovery, SuccessFactors, Executionis the Difference, BizX Mobile Touchbase, It’s time to love work again, SuccessFactors Jam andBadAss SaaS, and other SAP products and services mentioned herein as well as their respectivelogos are trademarks or registered trademarks of SAP AG in Germany or an SAP affiliate company.

All other product and service names mentioned are the trademarks of their respective companies.Data contained in this document serves informational purposes only. National product specificationsmay vary.

Disclaimer

These materials are subject to change without notice. These materials are provided by SAP AG andits affiliated companies (“SAP Group”) for informational purposes only, without representation orwarranty of any kind, and SAP Group shall not be liable for errors or omissions with respect to thematerials. The only warranties for SAP Group products and services are those that are set forth inthe express warranty statements accompanying such products and services, if any. Nothing hereinshould be construed as constituting an additional warranty.

g201311103942





g201311103942





About This HandbookThis handbook is intended to complement the instructor-led presentation of thiscourse, and serve as a source of reference. It is not suitable for self-study.

Typographic ConventionsAmerican English is the standard used in this handbook. The followingtypographic conventions are also used.

Type Style Description

Example text Words or characters that appear on the screen. Theseinclude field names, screen titles, pushbuttons as wellas menu names, paths, and options.

Also used for cross-references to other documentationboth internal and external.

Example text Emphasized words or phrases in body text, titles ofgraphics, and tables

EXAMPLE TEXT Names of elements in the system. These includereport names, program names, transaction codes, tablenames, and individual key words of a programminglanguage, when surrounded by body text, for exampleSELECT and INCLUDE.

Example text Screen output. This includes file and directory namesand their paths, messages, names of variables andparameters, and passages of the source text of aprogram.

Example text Exact user entry. These are words and characters thatyou enter in the system exactly as they appear in thedocumentation.

<Example text> Variable user entry. Pointed brackets indicate that youreplace these words and characters with appropriateentries.

2013 © 2013 SAP AG or an SAP affiliate company. All rights reserved. v





About This Handbook BW362

Icons in Body TextThe following icons are used in this handbook.

Icon Meaning

For more information, tips, or background

Note or further explanation of previous point

Exception or caution

Procedures

Indicates that the item is displayed in the instructor’spresentation.

vi© 2013 SAP AG or an SAP affiliate company.

All rights reserved. 2013





ContentsCourse Overview .......................................................... ix

Course Goals .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ixCourse Objectives ... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . x

Unit 1: Introduction........................................................ 1Evolution of HANA Landscapes... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2SAP HANA Basics .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .9SAP NetWeaver BW 7.3 ... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Unit 2: HANA-optimized DataStore Object and InfoCube ...... 33HANA-Optimized DataStore Object .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34HANA-Optimized InfoCube ... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54Semantically Partitioned Object.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72

Unit 3: Consuming HANA Models in BW ........................... 77VirtualProvider.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78TransientProvider .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84CompositeProvider .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91DB Connect .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .102

Unit 4: BI for BW powered by HANA ............................... 121BI for BW Powered by HANA ... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .122

Unit 5: SAP BW Workspace .......................................... 131SAP BW Workspace... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .132

Unit 6: Layered Scalable Architecture without SAP HANA ...165Layered Scalable Architecture without SAP HANA .... . . . . . . . . .166

Unit 7: Layered Scalable Architecture plus plus (LSA++) withSAP HANA ................................................................ 181

Layered Scalable Architecture plus plus (LSA++) with SAPHANA .... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .182

Unit 8: Exercises ........................................................ 219Exercises... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .221

Appendix 1: Analyze Requirements for the Case Study ....315

2013 © 2013 SAP AG or an SAP affiliate company. All rights reserved. vii





Contents BW362

viii© 2013 SAP AG or an SAP affiliate company.






Course OverviewTarget AudienceThis course is intended for the following audiences:

• BW Consultants• BW Project Managers• BW System Administrator

Course PrerequisitesRequired Knowledge

• Basic BW knowledge is mandatory.

Course Duration DetailsUnit 1: IntroductionEvolution of HANA Landscapes 15 MinutesSAP HANA Basics 15 MinutesSAP NetWeaver BW 7.3 15 Minutes

Unit 2: HANA-optimized DataStore Object and InfoCubeHANA-Optimized DataStore Object 15 MinutesHANA-Optimized InfoCube 15 MinutesSemantically Partitioned Object 30 Minutes

Unit 3: Consuming HANA Models in BWVirtualProvider 5 MinutesTransientProvider 5 MinutesCompositeProvider 10 MinutesDB Connect 10 Minutes

Unit 4: BI for BW powered by HANABI for BW Powered by HANA 15 Minutes

Unit 5: SAP BW WorkspaceSAP BW Workspace 15 Minutes

Unit 6: Layered Scalable Architecture without SAP HANALayered Scalable Architecture without SAP HANA 120 Minutes

Unit 7: Layered Scalable Architecture plus plus (LSA++) with SAPHANALayered Scalable Architecture plus plus (LSA++)with SAP HANA 120 Minutes

2013 © 2013 SAP AG or an SAP affiliate company. All rights reserved. ix





Course Overview BW362

Unit 8: ExercisesExercises Minutes

Course GoalsThis course will prepare you to:

• Run BW on InMemory Database (HANA)• Learn new function designed especially for BW HANA

Course ObjectivesAfter completing this course, you will be able to:

• Explain the BW on HANA Landscape.• Differentiate between HANA-Optimized Datastore Object and standard BW

Data Store Object.• Differentiate between HANA Optimized Info Cube and standard BW Info

Cube.• Explain the consuming of HANA models.• Describe BW powered by HANA.• Working with BW Workspace in the HANA environment.• Explain the Layered Scalable Architecture without SAP HANA.• Explain the new functionalities of Layered Scalable Architecture with SAP

HANA.

SAP Software Component InformationThe information in this course pertains to the following SAP Software Componentsand releases:

• SAP Business Information Warehouse 7.3 on SAP HANA 1.0

Important Information

It is strongly recommended to check necessary information publishedon the SAP Service Market Place. All information essential for coursepreparation like instructor guides, system setup guides, trouble shootingguides, logon information, and so on, you will find under the alias /curr-info(http://service.sap.com/curr-info).

In case you cannot access this site please ask the responsible education coordinator(the sender of this document) to make the relevant information available to you.

x© 2013 SAP AG or an SAP affiliate company.






http://service.sap.com/curr-info

Unit 11 Introduction

Unit OverviewContent of this unit is Introduction

Unit ObjectivesAfter completing this unit, you will be able to:

• Explain the SAP HANA Roadmap• Explain SAP HANA Basics• Give an overview on basic knowledge in SAP NetWeaver BW 7.3

Unit ContentsLesson: Evolution of HANA Landscapes ... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2Lesson: SAP HANA Basics.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .9Lesson: SAP NetWeaver BW 7.3... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

2013 © 2013 SAP AG or an SAP affiliate company. All rights reserved. 1





Unit 1: Introduction BW362

Lesson:2

Evolution of HANA LandscapesLesson Duration: 15 Minutes

Lesson OverviewEvolution of HANA Landscapes

Lesson ObjectivesAfter completing this lesson, you will be able to:

• Explain the SAP HANA Roadmap

Please refer to the regularly updated additional Instructor Guide provided onService Market Place (http://service.sap.com/curr-info)

Business ExampleYou want to use SAP HANA

Evolution of HANA Landscapes

Figure 1: HANA Development Start

In the exclusive consideration of the aspect of data storage would be a databasethat stores data in main memory and can answer structured queries, the goal.However, applications spend only a small percentage of their time access to data.In fact, many applications have processes that need access to as much data thatthe passage of time when transferring the data is immense. In addition, complex

2© 2013 SAP AG or an SAP affiliate company.






http://service.sap.com/curr-info

BW362 Lesson: Evolution of HANA Landscapes

handling routines need to be implemented, which can deal with these datavolumes. Applications read in the traditional 3-tier architecture (data, application,presentation layer), the first data from a database, process them in its memory andwrite results back either in the database or provide it to the presentation layer.Given the immense amount of data that produce current business software, sensorsand social networks, this concept is becoming increasingly problematic. Willyou now have to evaluate the volume of data very quickly and deliver results onmobile platforms, it is no longer viable. In-memory techniques but have all thedata in memory, and modern computer systems have many computing cores,providing an impressive performance. Therefore, it is obvious not to move thedata, but the instructions. Why not a complex process in the memory instead ofthe application layer in which the data storage layer execute? Under the slogan“In-Memory Computing” SAP persecuted an approach to transfer data-intensiveprocesses from the application to the storage layer and perform there. Thus, forexample, the software giant intends to be able to make business processes, whichhave in the past run by the performance limitations of many databases either onlyon weekends in a batch process or were not to be realized.

Figure 2: Todays Situation – without HANA







Figure 3: Application View – HANA 1.0 SP02

SAP HANA is a completely re-imagined platform for real-time business. Ittransforms business by streamlining transactions, analytics, planning, predictive,sentiment data processing on a single in-memory database so business can operatein real-time.

• Innovations can also be used in a side-by-side scenario limiting theimplementation efforts and risk to the existing core processes

• Side-by-side solutions can be retrofitted at a later point, as required

Figure 4: Application View – HANA 1.0 SP03








SAP Netweaver BW Powered by HANA has now been on the market since April10, 2012 and we have seen huge interest from customers who want to execute theirEDW strategy with BW powered by HANA. However, with this new release hascome a number of questions from customers that want to know more about themarriage of BW and HANA such as: Are InfoCubes still required; what modelingobjects are available for mixed scenarios: what is next for BW in terms of aroadmap? Attached is a updated presentation of BW powered by HANA that willhelp you better understand this exciting new release.

HANA as the Primary Database for BW and Foundation for new Applications

• In-Memory database used as primary persistence for BW• BW is becoming a HANA optimized EDW• BW continues to manage the analytic metadata and the data provisioning

processes• HANA provides all the functionality of BWA and more• High-performance foundation for new SAP applications

Figure 5: Application View – ERP and BW on HANA XX

• Porting ERP / Suite on SAP HANA• Flexible, view-based analytics with enriched openness for customers• Allow for reuse of Side-by-Side apps







Figure 6: Technical Architecture Patterns

Figure 7: SAP HANA Innovation Overview

SAP is delivering a new class of solutions on top of the SAP HANA platformthat provide real-time insights on big data and state-of-the-art analysis; such asmachine learning, pattern recognition, and predictive capabilities.

These solutions can empower companies to transform the way they run theirbusiness, from enabling rapid, sense-and-respond processes and targeted actions,to even rethinking their business models. We distinguish between, Applications,








powered by SAP HANA which provide a rich set of functionalities that addressesa company’s existing business processes and enables innovations in processes andbusiness models (e.g. SAP Smart Meter Analytics powered by SAP HANA);applications provide business logic, user interface, workflow, and other capabilitiesand are optimally designed to run natively on the SAP HANA platform to fullyutilize its in-memory computing capabilities (e.g., business logic executed inthe database layer).

In addition there are accelerators and analytic content available. Acceleratorsare software that utilizes the power of SAP HANA to dramatically improve theperformance of existing SAP Business Suite functionality in small, well-definedareas that bring immediate value to customers. The Customer SegmentationAccelerator that we are focusing on today is such an example and follows the SAPCO-PA Accelerator powered by SAP HANA.

Analytic Content is complementary software that complements SAP applicationsand supports the customer’s integration, implementation, and configurationactivities. Analytic content provides pre-built reporting, dashboards, and datamodels that run natively on the SAP HANA platform (e.g. Operational Reportingpowered by SAP HANA). In the near future, SAP plans to provide unrestrictedSAP HANA powered applications, accelerators and analytic content for Lines ofBusiness that improve enterprise planning and performance management, businessplanning and consolidation as well as customer planning and intelligence.

In addition, several industry applications, especially for Banking, Retail,Consumer Products and Utilities, are planned to bring real-time processing on BigData to key industry specific processes. In order to ensure quicker time to valuesome of these solutions, including the SAP Financial and Controlling Acceleratorare also delivered as rapid-deployment solutions. The SAP Rapid Deploymentsolutions provide maximum predictability with a fixed cost and scope.







Lesson Summary

You should now be able to:• Explain the SAP HANA Roadmap







BW362 Lesson: SAP HANA Basics

Lesson:9

SAP HANA BasicsLesson Duration: 15 Minutes

Lesson OverviewSAP HANA Basics


• Explain SAP HANA Basics

[Enter a description of what the instructor should discuss with the participantsabout the context of the lesson. ]

Business ExampleYou want to know the HANA Basics

Figure 8: In-Memory Computing







Figure 9: HANA Performance

This is tremendous. 12000 times faster on an average of 29 customers acrossindustries is real-time! Depth and breadth of SAP HANA. I am sure all of yousitting here would be able to identify your industry and relate to the gain HANAprovides!

Figure 10: SAP HANA Data

In simplified terms means 64-bit processors that are designed by their ALUconstruction so that 64 bits (8 bytes) can be processed simultaneously or duringa cycle. This includes the external and internal design of data and address bus,the width of the register set with one. Furthermore, the instruction set is usuallydesigned consistently on 64-bit, unless a backward-compatible legacy (see X86








architecture) are present. This applies similarly to the standard addressing modes,the bit width of the arithmetic logic unit (ALU), in principle, may differ from theaddress of the unit (as with most 64-bit CPUs).

In order to provide more acceleration in data processing, manufacturers havecome up with different acceleration techniques: These range from the reduction ofwrite operations on the outer tracks of the disk sectors on the preprocessing of thedata in or or on the hard drive itself to large caches that are designed to reducethe actual number of hits on hard drives. These techniques have one thing incommon: In essence, they assume that data is stored on the hard drives, and theyare trying to speed up access. Memory is now available not only in much largercapacities than before, he is now also affordable and thanks to modern 64-bitoperating systems in the first usable. With the 32-bit address space is limited tofour gigabytes of memory, while one with 64-bit addressing can use so muchmemory that it still does not fit into a server.

However, all data in main memory would be useless if the CPU does not haveenough power possessed to process this data. Namely, if the processing speed ofthe CPU is so slow that a read from a hard drive is fast enough to not have to be alldata already in memory. At this point there has been in recent years a great changeof complex CPUs to multi-core processor units. This Reckoner have up to tencores and can be for two, four or eight built into a server. So wait on every shot,the heart of a computer beats, up to 80 data intensive computing cores on newdata or instructions. For this computing power, it is necessary to write specificsoftware. This has complex tasks into many small process strands (threads) canbreak, which can utilize the large number of parallel cores. For optimal processingof the data is also fast enough to provide optimized data structures.

Figure 11: Hardware Rethink







Techniques are irrelevant to dealing with the acceleration reading from hard drivesand other relevant, which deal with the rapid exchange of information betweenmain memory and CPU registers. In the words of the database expert Jim Gray,the technology has moved a step closer to the CPU “is RAM disk, disk is tape,and tape is dead”.

Figure 12: Scale – SW Side Distribute Across Cores

Figure 13: Fast – SW Side Optimization for Memory

Assume that we want to aggregate the sum of all sales amounts in the example infigure 2 using a row based table. Data transfer from main memory into CPU cachehappens always in blocks of fixed size called “cache lines” (for example 64 bytes).With row based data organization it may happen that each cache line contains only








one “sales” value (stored using 4 bytes) while the remaining bytes are used for theother fields of the data record. For each value needed for the aggregation a newaccess to main memory would be required.

This shows that with row based data organization the operation will be sloweddown by cache misses that cause the CPU to wait until the required data isavailable. With column-based storage, all sales values are stored in contiguousmemory, so the cache line would contain 16 values which are all needed for theoperation. In addition, the fact that columns are stored in contiguous memoryallows memory controllers to use data prefetching to further minimize the numberof cache misses.

Figure 14: Column Store High Lights

The column store uses efficient compression algorithms that help to keep allrelevant application data in memory. Write operations on this compressed datawould be costly as they would require reorganizing the storage structure.

Therefore write operations in column store do not directly modify compresseddata. All changes go into a separate area called the delta storage. The delta storageexists only in main memory. Only delta log entries are written to the persistencelayer when delta entries are inserted.

Delta merge operation:

• The delta merge operation is executed on table level.• Its purpose is to move changes collected in write optimized delta storage into

the compressed and read optimized main storage.• Read operations always have to read from both main storage and delta

storage and merge the results.• The delta merge operation is decoupled from the execution of the transaction

that performs the changes. It happens asynchronously at a later point in time.







Delta merge is triggered by one of the following events:

• Number of lines in delta storage for this table exceeds specified number• Memory consumption of delta storage exceeds specified limit• Merge is triggered explicitly by a client using SQL• The delta log for a columnar table exceeds the defined limit. As the delta

log in truncated only during merge operation, a merge operation needs to beperformed in this case.

• Triggering a Delta Merge (When Using the SAP HANA Database)• http://help.sap.com/saphelp_nw73/help-

data/en/62/9d41934c0744ef9a8f21fa4c70baa3/frameset.htm

Figure 15: Modeling for HANA 1.0 – Using SAP HANA Studio

Attribute View

An attribute view is used to model an entity based on the relationships betweenattribute data contained in multiple source tables.

For example, customer ID is the attribute data that describes measures (that is,who purchased a product). However, customer ID has much more depth to it whenjoined with other attribute data that further describes the customer (customeraddress, customer relationship, customer status, customer hierarchy, and so on).







http://help.sap.com/saphelp_nw73/helpdata/en/62/9d41934c0744ef9a8f21fa4c70baa3/frameset.htm

http://help.sap.com/saphelp_nw73/helpdata/en/62/9d41934c0744ef9a8f21fa4c70baa3/frameset.htm


You create an attribute view to locate the attribute data and to define therelationships between the various tables to model how customer attribute data, forexample, will be used to address business needs. You can model the followingelements within an attribute view:

• Simple attributes• Calculated attributes• Hierarchies note

Analytic View

An analytic view is used to model data that includes measures.

For example, an operational data mart representing sales order history wouldinclude measures for quantity, price, and so on.

The data foundation of an analytic view can contain multiple tables. However,measures that are selected for inclusion in an analytic view must originate fromonly one of these tables (for business requirements that include measure sourcedfrom multiple source tables, see calculation view).

Analytic views can be simply a combination of tables that contain both attributedata and measure data. For example, a report requiring the following:

Customer_ID Order_Number Product_ID Quantity_Ordered Quantity_Shipped

Optionally, attribute views can also be included in the analytic view definition. Inthis way, you can achieve additional depth of attribute data can be achieved. Theanalytic view inherits the definitions of any attribute views that are included inthe definition. For example:

Customer_ID/Customer_Name Order_Number Product_ID/Product_Name/Prod-uct_Hierarchy Quantity_Ordered Quantity_Shipped

You can model the following elements within an analytic view:

• Simple attributes• Calculated attributes• Private attributes• Simple measures• Calculated measures• Restricted easures







Figure 16: Modeling for HANA 1.0 – Using SAP HANA Studio

Calculation View

A calculation view is used to define more advanced slices on the data in SAPHANA database. Calculation views can be simple and mirror the functionalityfound in both attribute views and analytic views. However, they are typically usedwhen the business use case requires advanced logic that is not covered in theprevious types of information views.

For example, calculation views can have layers of calculation logic, can includemeasures sourced from multiple source tables, can include advanced SQLlogic, and so on. The data foundation of the calculation view can include anycombination of tables, column views, attribute views and analytic views. You cancreate joins, unions, projections, and aggregation levels on the sources.

You can model the following elements within a calculation view

• Simple attributes• Calculated attributes• Private attributes• Simple measures• Calculated measures• Restricted measures• Counters• Hierarchies (created outside of the attribute view)








Figure 17: SQL Script – New Programming Model

Functional extension – allows the definition of (side-effect free) functions whichcan be used to express and encapsulate complex data flows

Data type extension – allows the definition of types without corresponding tables

Figure 18: Column Views in SAP HANA – Run-Time and Design-Time Objects







Figure 19: How to Build and Consume Content for SAP HANA Appliance








Lesson Summary

You should now be able to:• Explain SAP HANA Basics







Lesson:20

SAP NetWeaver BW 7.3Lesson Duration: 15 Minutes

Lesson OverviewSAP NetWeaver BW 7.3


• Give an overview on basic knowledge in SAP NetWeaver BW 7.3


Business ExampleBased on a change to SAP HANA you must know about some SAP BW basics.







BW362 Lesson: SAP NetWeaver BW 7.3

SAP NetWeaver BW 7.3

Figure 20: SAP NetWeaver Business Warehouse – EDW Model and DataflowDefinition

Define a central EDW model that satisfies the need of decision makers across allareas of a company and acts as a single point of truth for any kind of information

• Dataflow Modeler

Define ETL processes to populate the persistency layers of the EDW Modelwith cleansed and consolidated, consistent and harmonized data in an adequateperiodicity, will say periodically based on batch or near-real or real time processes

• Transformations / DTP• Source System handling• Realtime Data Acquisition (RDA)







Figure 21: SAP NetWeaver Business Warehouse – Scheduling andMonitoring the Dataflow

Organize, schedule and monitor the dataflow towards and within the EDW andprovide tools to repair or redo unexpected failures during load processes.

• External ETL Processes• Metadata Management• Process Chains• Admin Cockpit• Generating Repair Chains• Checking Error DTPs

Use the software to design and deploy projects quickly, and to address dataquality and integration with one solution. Your users can manage data acrosscritical business processes and collaborate between business and IT, supporting asingle project or a larger data governance initiative. For a more complete viewof business, the software delivers native support for free-form data, structureddata, and unstructured text data.

With SAP BusinessObjects Data Services, you can assess and improve dataquality with a comprehensive solution that supports data within any industry,locality, or data domain, including customer, product, supplier, and material data.Virtually all data – including free-form, structured, and unstructured data – can beprocessed and cleansed. Business user interfaces, designed to be intuitive, allow








you to standardize, correct, and match data to reduce duplicate information and toidentify relationships. Extensive global support comprises data quality coveragein more than 230 countries – including an exclusive partnership with China Post.

Figure 22: SAP NetWeaver Business Warehouse – EDW Persistency andPerformance Management

Provide Data Management capabilities in order to massage the data persistencyaccording to the specific characteristics of the data and information partitions suchas actual, frequently asked data, volatile data that is going to be updated verylikely, old, read only data – with nearly no demand for reporting, data that has tobe hidden but kept for legal reasons.

Provide a technology for high performance OLAP processing on top of all parts ofthe data resulting out of adequate modeling features (like Star Schema), particularpersistency layers in the model (granular vs. aggregated data resp. information)and sophisticated storage paradigms







Figure 23: Database Shared Library (DBSL) – Platform Concept SupportingStandard RDBMS

The database-dependent part of the SAP database interface can be found in itsown library that is dynamically linked to the SAP kernel. This database librarycontains the Database Shared Library (DBSL), as well as libraries belonging to thecorresponding database manufacturer. These are either statically or dynamicallylinked to the database library.

Missing analytical capabilities on DB level lead to massive AppServer/DBServertraffic

• DataStoreObjekt (DSO) (e.g. Activation)• Integrated Planning (e.g. Disaggregation)

Distributed data management (RDBMS vs. BWA vs. NLS vs. Archive)

• Missing data aging strategies in RDBMS

Nature of RDBMS – tupel based data storage, indexing necessary for performance

• Read/Load Performance on the RDBMS (e.g. Extended SAP Star Schematoo complex)








Other Examples

• Exception Aggregation (e.g.Distinct Count only available as BWACalculation Engine feature)

Figure 24: SAP NetWeaver BW Accelerator 7.20

Figure 25: Application vs. Database Server – Technical Overview

With large data volumes, reading information becomes a bottleneck







Next generation applications will delegate data intense operations

The runtime environment executes complex processes in memory

In memory computing returns results by pointing apps to a location in sharedmemory

Figure 26: SAP NetWeaver BW, Powered by SAP HANA

Enhanced built-in analytical capabilities

• Full database functionality• Full BWA functionality

Advanced features

• HANA-optimized InfoCube• HANA-optimized DataStore Objects• Publishing SAP HANA models into BW








Figure 27: System Upgrade: Necessary Steps

Sizing

Starting with version 7.30 SP5 you can run SAP Business Information Warehouse(SAP BW) on SAP HANA as database platform. This enables you to leverage theIn-Memory capabilities of HANA and the SAP-HANA-optimized BW objects.Note that for a stand-alone version of SAP HANA (i.e. HANA without BW)separate sizing information is available in note 1514966.

If you want to migrate an existing SAP NetWeaver BW system from any databaseplatform to HANA, we strongly recommend using the new ABAP sizing reportfor SAP NetWeaver BW described in SAP note 1736976 which – providesmuch better accuracy of sizing results

• Handles source database compression auto• Uses table type specific compression factors• Considers sizing effects of the concept of non-active data (version 1.3)• Produces much more detailed results than the attached database specific

scripts, facilitating the selection of a suitable hardware configuration

New report /SDF/HANA_BW_SIZING describes in note 1736976 and you canfind additional PDF files there







Figure 28: Traditionell Approach

Figure 29: New DataWarehousing Approach incl. HANA Technologie

Reduction data replication

Higher compression and significant persistent lower data volume

Fast Mainteneance including prototyping and testing








Reduced HW-Footprint

Reduced TCO: Fast Implementation and simple Administration (DB)

Improved load performance for DSOs

Exzellente Query Performance

Accelerated HANA-Planung

Migration without New Implementation – no interrupts for current scenarios







Lesson Summary

You should now be able to:• Give an overview on basic knowledge in SAP NetWeaver BW 7.3







BW362 Unit Summary

Unit SummaryYou should now be able to:• Explain the SAP HANA Roadmap• Explain SAP HANA Basics• Give an overview on basic knowledge in SAP NetWeaver BW 7.3






Unit Summary BW362







Unit 231 HANA-optimized DataStore Object

and InfoCube

Unit OverviewContent of this unit is HANA-optimized DataStore Object and InfoCube


• Explain the motiviation for HANA optimized DataStore Objects• Identify the difference in the architecture and structure compared with

DataStore Objects stored in a relational database• List the different Conversion options• Elaborate the typcial business scenarios where HANA optimized DataStore

Objects can be used in• Understand the motivation for SAP HANA optimized InfoCubes• Identify the difference in the architecture and structure compared with

InfoCubes stored in a relational database• Describe the Conversion process• Elaborate the typcial business scenarios where SAP HANA optimized

InfoCubes can be used in• Describe the use cases of an SPO• Create an SPO and integrate it into the data flow

Unit ContentsLesson: HANA-Optimized DataStore Object .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34Lesson: HANA-Optimized InfoCube... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54Lesson: Semantically Partitioned Object .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72






Unit 2: HANA-optimized DataStore Object and InfoCube BW362

Lesson:32

HANA-Optimized DataStore ObjectLesson Duration: 15 Minutes

Lesson OverviewHANA-Optimized DataStore Object


• Explain the motiviation for HANA optimized DataStore Objects• Identify the difference in the architecture and structure compared with


Objects can be used in


Business ExampleYour company has built a large Enterprise Data Warehouse system based on theSAP BW. With the invention of SAP HANA you decided to benefit the most its‘In-Memory capabilities. After analysing your dataflow in the SAP BW system,you identified the DataStore Objects as the first objects to be explored. Youenvisage to migrate some of your existing DataStore Objects in your dataflowto SAP-HANA optimized ones as well as using the SAP HANA-optimizedDataStore Objects in newly created dataflows.







BW362 Lesson: HANA-Optimized DataStore Object

HANA-Optimized DataStore Object

Figure 30: Motivation

The HANA-optimized DataStore Objects leverage SAP HANA technology to

• Reduce the amount of physical storage• Accelerate data loads• Allow faster Remodeling of structural changes

No adoption of processes, MultiProvider, Queries required







Figure 31: General Description

The SAP HANA-optimized DataStore object is a standard DataStore object that isoptimized for use with the SAP HANA database. By using SAP HANA-optimizedDataStore objects, you can achieve significant performance gains when activatingrequests. The change log of the SAP HANA-optimized DataStore object isdisplayed as a table on the BW system. However, this table does not save any data,which helps to save memory space. When the change log is accessed, the datacontent is calculated using a calculation view. Data is read from the history tablefor the temporal table of active data in the SAP HANA database.

Note: If you want to view the change log data in the ABAP Dictionary, awarning appears explaining that the table does not exists in the database.This is due to optimization – the table in the database is replaced by acalculation view.








Figure 32: DataStore Objects in SAP NetWeaver BW 7.30 – Creation ofConsistent Delta Information

Figure 33: SAP BW – DataStore Objects – Main Principles







Figure 34: HANA-Optimized DataStore Objects – Overview and Design

Figure 35: SAP HANA-optimized DataStore Objects – Mapping BetweenApplication Server and HANA DB

The table for active data is a temporal table that consists of three components:History table, main table and delta table. Data activation is started on the BWsystem and executed in SAP HANA. No data is transferred to the applicationserver during activation.








On the DataStore object editing screen, you can choose the Unique Data Recordsproperty. However, this does not improve system performance when using an SAPHANA-optimized DataStore object. The uniqueness of the data is not checked,meaning that data consistency cannot be guaranteed.

Figure 36: HANA-optimized DataStore Objects – Performance Numbers (LabResults, Record Size ~1KB, Runtime in Seconds)

Figure 37: Standard DataStore Object (NOT HANA-optimized) Active Tableand Change Log Table







Figure 38: SAP HANA-Optimized DataStore Object – DB Status and theAdditional Field

Differences to a Normal Standard DataStore Object

The SAP HANA-optimized DataStore object contains the additional fieldIMO__INT_KEY in the active data table. This field is required for optimizingSAP HANA and is hidden in queries.

A before/after image is still written during activation, even if no changes aremade to the active data.

It cannot be used as a source of update flows in a 3.x data flow. More information:Data Flow in Business Warehouse

The complete history of a request is not saved.

Only the start status and end status (relating to an activation) are saved.

Since real-time data acquisition (RDA) usually involves small data volumes foreach activation step, SAP HANA optimization does not produce any advantages.The use of SAP HANA-optimized DataStore objects for RDA is therefore notsupported.








Figure 39: SAP HANA-Optimized DataStore Object – Active Table in theHANA Studio

Figure 40: SAP HANA-Optimized DataStore Object – Change Log in theHANA Studio







Figure 41: HANA-Optimized DataStore Object – Conversion

If you are using a SAP HANA database and want to benefit from it whenloading data into DataStore objects, we recommend converting existing standardInfoCubes. After migration to the SAP HANA database, normal standardDataStore objects are contained in the SAP HANA database’s column-based store.

Prerequisites

DataStore objects can only be converted to SAP HANA optimized DataStoreobjects if:

• They are not part of a HybridProvider.• They are not integrated into a 3.x dataflow. This basically means that the

dataflow from the DataStore object to other InfoProviders must be a newdataflow. The dataflow to the DataStore object could also be a 3.x dataflow.We recommend migrating to the new dataflow however. More information:Migrating a Data Flow

• They are not supplied with data using real-time data acquisition (RDA).








Procedure

1. There are two ways of calling the conversion transaction:

• You are in the DataStore object editing screen. Choose – Goto –Conversion to SAP HANA-Optimized. The system displays theDataStore object to be edited.

• Call transaction RSMIGRHANADB directly.2. You can now use input help to select DataStore objects for conversion.3. You have the following options:

• Without change log: In this case, only the table of active data isconverted. The change log is empty after conversion is finished. Youshould therefore ensure that all delta requests are updated beforeconversion takes place. This conversion option is faster, but has thedisadvantage that old requests cannot be rolled back.

• Reconstruct change log:

A new change log is created. This option takes more time.

Note: If you have already archived data from the DataStoreobject, you can only restore requests that do not belong to thearchived area. This means that the reconstructed change logmight contain fewer requests than the original one.

• Package size for data transfer: If the conversion breaks down, apackage size should be defined that the data can be processed with. Ifno package size is defined, the conversion is performed in a transaction.

4. You can specify whether the log is displayed after conversion.5. Choose Execute. The DataStore objects are converted. While the conversion

is running, a lock is set so that no changes (for loading data, for example)can be made to the DataStore object.







Figure 42: HANA-Optimized DataStore Objects – Benefits

Figure 43: Performance Improvements – Overall DataFlow, Process Chain








Figure 44: Limitations and Features

For certain requirements, the role of the classical Reporting layer (query optimizedInfoCubes) might diminish. DataStore Object might be able to provide sufficientquery performance to omit InfoCubes.

Nevertheless, the semantic separation of data and query structure via MultiProviderwill not become obsolete.

In cases where the DataStore Object Activation time is the bottleneckin the overallstaging process, the SAP HANA-optimized DataStoreObjects will acceleratethe staging processing.

The reduced DB space consumption of the SAP HANA-optimized DataStoreObject helps to control data growth.

Figure 45: Partitioning of Write-Optimized DSOs







Better performance of write-optimized DataStore Objects

• Write-optimized DSO are now partitioned by request-ID• Partitioning improves merging performance significantly, especially in case

the delta Index is merged for a large Write-Optimized DSO• With partitioning only the relevant (last) partition (with changed/new

records) is merged• In addition performance for read and delete is improved, because with

partition pruning only a subset of the data is accessed

Figure 46: State of Data

Active + Non-Active + NLS

HOT

• Data is read/written frequently• In Memory, additional memory required for dynamic objects (merge,

intermediate results, etc.)

WARM

• Mostly read access – lookups, transformations, etc.• In Memory, no additional memory required for dynamic objects

COOL

• Infrequent access – no need to keep in memory all the time• On disk, loaded to memory only on demand, good candidate for displacement

if memory runs short








COLD

• Infrequent access, restricted to [BW] NLS capabilities – not stored in HANApersistence

• In NLS subsystem only – data volume not considered in HANA sizing

Hint: Non-active Data concept is reflected in the last version (V1.3) ofSizing Report

Optimized usage of HANA memory resources

Modeling of LSA concepts (Corporate Memory, …) by specifying objectsthat are supposedto be handled as “warm” or “cool”

See note 1736976 for more details about the Sizing Report

Tables/partitions in SAP HANA can be marked as “non-active” (“cool”)

Such tables/partitions are …

• Loaded into RAM only when accessed• Loaded into RAM in case of read access (column-wise) and processed as

usual (same speed and functionality)• Loaded to RAM for merge process (if new data was written and delta reaches

limit)• Displaced from RAM with highest priority in case of RAM shortage (but

only then) or when actively a cleanup is triggered

BW automatically marks all PSA tables and write-optimized DSOs (except theirlatest partitions) as “cool”, so no extra maintenance or tuning is necessary. Allother BW objects are treated as before.

In addition, customers can override the handling of write-optimized DataStoreobjects (e.g. those which are used to build a Corporate Memory layer withinan LSA).

Customers need to actively define their “warm” and “cool” data objects (bothin sizing report and in BW metadata).

See note 1767880 for more details.

In detail – non-active data concept for BW on SAP

Large BW systems contain large amounts of data that are no longer or rarelyactively used but that should remain in the system (historical data, keeping datafor legal reasons, and so on). This data is callednon-active data in the following.







To optimize utilization of the main memory, you want to make sure the followingfor non-active data:

• If the main memory has sufficient capacity, non-active data is availabledirectly in the main memory.

• When there are bottlenecks in the main memory, it is preferably non-activedata that is removed from the main memory.

• If you access non-active data that is not available in the main memory,the system only loads the smallest possible amount of data into the mainmemory. (Basically, the columns of the relevant partition)

This makes sure there is an optimal access to data that is relevant for reporting andprocesses because this is almost always availablein the main memory. Also, youcan reduce the main memory for sizing if the share of non-active data is very large.

HOT data: Data that is accessed very often, for example, for reporting orforprocesses in warehouse management. (queries for InfoCubes, DataStore objects,activation of data in a standard DataStore object)

WARM data: Only certain columns of the object are accessed. This means thatthere are columns that are no longer or rarely accessed (mostly lookups withtransformation rule type, or specific columns in routines).

COOL data: These columns are no longer or rarely accessed. (write-optimizedDataStore objects of the corporate memory, or Persistent Staging Areas orwrite-optimized DataStore objects of the acquisition layer)

COLD data: Data of a BW system that is no longer required, and that can beorwas archived or saved using Nearline Storage.

Optimization of the data stores with regard to non-active data

In a BW system, most data with the classification COOL and WARMin thePersistent Staging Areas of the DataSources and in write-optimized DataStoreobjects of the acquisition layer and the corporate memory. These objects oftencontain data that is no longer used, however, newdata is loaded to these objectson a daily basis. As a result, the period of time since the last usage is normallynot longer than 24 hours. Despite this, it should be rather such objects that areremoved from the memory than objects that, for example, are used for reporting.You should also avoid that the data that is no longer used is loaded to the mainmemory when loading new data.

How Persistent Staging Areas and write-optimized DataStore objects have beenoptimized with regard to non-active data is described in the following. Forthis, it is first explained how displacement works on the SAP HANA database(DB) in general. Moreover, request partitioning of Persistent Staging Areas andwrite-optimized DataStore objects,and the early unload setting are explained.

Displacement:








Displacement of columns of a partition is carried out if a bottleneck occurs in themain memory, this means if usage of main memory by a database process exceedsa threshold value. SAP HANA DB uses last-recently-used concept for displacingtable columns. First of all, the columns of a table partition are removed fromthemain memory whose data has not been accessed for the longest period of time.

Partitioning of the Persistent Staging Area and of the write-optimizedDataStore objects based on the requests.

The Persistent Staging Areas of DataSources and the write-optimized DataStoreobjects are created on the database in partitions by the request. With the restrictionthat duplicate data records have to be allowed for write-optimized DataStoreobjects (setting in the maintenance dialog). Partitioning by request means thata request is completely written to a partition. If the threshold value of fivemillion lines (for write-optimized DataStore objects 20 million) is exceeded, anew partition is created and the data of the next request is written to this newpartition. As a result, normally only the data from the newest partitions is accessedby data warehousing processes (loading data and reading data) because theseprocesses always specify precisely the partition ID for table operations, and asa consequence, no data from other partitionshas to be accessed. CAUTION Forwrite-optimized DataStore objects that are connected to 3.x data flows (inbound oroutbound update rules), the system always loads all the data to the main memorybecause no partition ID is used to access the data. Write-optimized DataStoreobjects with a semantic key, for which duplicate data records are not allowed,are not partitioned by request. As a result, all data is always loaded to the mainmemory when accessing theobject.

Setting EARLY UNLOAD of a table in the SAP HANA DB

For some BW objects, you can make the EARLY UNLOAD setting. If abottleneck occurs in the main memory, the data of an object that is flagged in sucha way is prioritized for displacement from the main memory. For these objects,the time that has passed since the last usage is by default multiplied by 27. As aconsequence, these objects are displacedquicker than objects that have not beenaccessed for a long time but that do not have this setting.

Implementation of non-active data in BW:

As of Support Package 08 and SAP HANA Support Package 05, the “non-activedata” concept is introduced in the BW system due to the following settings thatare implemented in the system automatically. Persistent Staging Area tables andwrite-optimized DataStore objects are flagged as EARLY UNLOAD by default.This means that these objects are displaced from the memory before other BWobjects (such as InfoCubes or standard DataStore objects).

Persistent Staging Areas and write-optimized DataStore objects are alsopartitioned by request:

Partitions that have once been displaced are no longer loaded because new data isloaded only to the newest partition, and older data is normally no longer accessed.







However, if old data should be accessed, this data is loaded tothe main memory.Typically, it is load processes that are used for setting up new target objects, ordata has to be reloaded. For such processes,it is acceptable that the data mustfirst be loaded to the main memory. If only certain columns are accessed in thedisplaced objects, only these columns are loaded to the main memory. The othercolumns remainon the disk. (for example, lookups in transformations that selectonlycertain columns).

Due to this concept, the main memory resource management is improved using anautomatism. This affects sizing. If Persistent Staging Areasand write-optimizedDataStore objects contain large amounts of non-active data, this data remains onthe disk, and the main memory can be chosen smaller correspondingly.

Caution: The BW system is optimized in such a way that PersistentStaging Areas and write-optimized DataStore objects are accessed onlywith the respective partition ID, so that not the complete table has to beloaded to the main memory. Avoid in any case to access such tablesusing regular manual accesses (SQL editor or transaction SE16), or usingyourown source code. This would load the complete table to the mainmemory.

EARLY UNLOAD for other BW objects

You can also flag InfoCubes and other DataStore objects as EARLY UNLOAD.However, we generally do not recommend this. Since these objects are notpartitioned by request, the complete object is loaded to the main memory, or it isnever displaced because it is accessed too often (for example, by a daily loadingprocess). This can even lead to counterproductive behavior if they are displaceddue to the EARLY UNLOAD flag, but then are reloaded to the main memory ashort time later for a loading process or a query. As a consequence, you shouldonly use this setting in a very restricted manner for such objects. (For example,if an InfoCube exists for everyyear, but you only report to the current year. ForInfoCubes from the past years, you could make this setting because they are nolonger connected toloading processes, and no reporting is carried out.)

Effects on hardware sizing of SAP HANA DB

This concept improves main memory resource management, which has positiveeffects on hardware sizing for a large amount of non-active data. For moreinformation about this, see SAP Note 1736976. CAUTION However, you haveto fill in the sizing report with input that matches reality. If data is classifiedincorrectly, and is used frequently despite this, significant problems may occur inmainmemory management if continuously insufficient amounts of main memoryare available.

FAQ:








How can I set or reset the EARLY UNLOAD behavior for BW objects? PersistentStaging Areas and write-optimized DataStore objects are set to EARLY UNLOADby default. You can use transaction RSHDBMON to reset this behavior or to set itfor other BW objects.

Is the EARLY UNLOAD behavior also provided for other tables (such as Ztables)? No; other database tables are not supported.

Are there restrictions for tables that are flagged with EARLY UNLOAD? No;there are no general restrictions. When accessing data of these objects, these mayfirst be loaded from the disk to the main memory.

How does this concept affect main memory sizing for SAP HANA DB? PersistentStaging Areas and write-optimized DataStore objects that are COOL or WARMin terms of usage enter sizing with a correspondingly lower factor. See sizingnote 1736976.

Is this concept valid for 3.x data flows? No; for 3.x data flows, the partition ID isnot used when accessing the data, so that all the data has always to be reloaded tothe main memory.

Will this concept be extended to further BW objects or databasetables? Yes; thetreatment of non-active data is optimized further, be it by extending this conceptor by using new technologies or concepts.

Solution







Procedure for activating the “non-active data” concept:

• Import SAP HANA Support Package 05• Import Support Package 9 for SAP NetWeaver BW 7.30 (SAPKW73009)

into your BW system. The Support Package is available when SAP Note1750249 “SAPBWNews NW 7.30 BW ABAP SP9”, which describesthis Support Package in more detail, is released for customers or importSupport Package 6 for SAP NetWeaver BW 7.31 (SAPKW73106) into yourBW system. The Support Package is available when SAP Note 1753103“SAPBWNews NW BW 7.31/7.03 ABAP SP6”, which describes thisSupport Package in more detail, is released for customers.

• Restart program RS_BW_POST_MIGRATION so that Persistent StagingArea tables are classified correctly (unload Priority 7, see SE14). It issufficient to run the report exclusively with option 14 (set unload priority). Ifa migration has been carried out from a different database to BW on SAPHANA, and BW Support Package 09 is contained, a single default run ofthe report is sufficient.

• Run the program RSDU_WODSO_REPART_HDB for all relevantwrite-optimized DataStore objects so that these are partitioned and classified(unload Priority 7). Objects that have small amounts of data or that are in adistributed SAP HANA DB landscape are already classified and partitionedby the program RS_BW_POST_MIGRATION. See SAP Note 1776749 also.

• After you carry out the mentioned steps, all the data from Persistent StagingAreas and write-optimized DataStore objects that is rarely used is displacedautomatically with a higher priority. As of this point in time, the process iscompletely automatic; there is no further maintenance required for existingor new tables.








Lesson Summary

You should now be able to:• Explain the motiviation for HANA optimized DataStore Objects• Identify the difference in the architecture and structure compared with


Objects can be used in







Lesson:52

HANA-Optimized InfoCubeLesson Duration: 15 Minutes

Lesson OverviewHANA-Optimized InfoCube


• Understand the motivation for SAP HANA optimized InfoCubes• Identify the difference in the architecture and structure compared with


InfoCubes can be used in


Business ExampleYour company has built a large Enterprise Data Warehouse system based on theSAP BW. After the invention of SAP HANA you decided to benefit the mostfrom the In-Memory capabilities.

After upgrading your SAP BW system to a HANA DB based SAP BW system, allnewly created InfoCubes will be SAP HANA optimized.

In addition you have to decide which of the existing InfoCubes should beconverted to benefit from the HANA capabilities.







BW362 Lesson: HANA-Optimized InfoCube

Motivation

Figure 47: Motivation

Figure 48: General Description

Figure 49: SAP HANA-Optimized InfoCube – From Snowflake to Star Schema







SAP HANA-Optimized InfoCube in the System

Figure 50: Standard InfoCube (not SAP HANA-Optimized)

An InfoCube is a type of InfoProvider. It describes a closed data set (from ananalysis point of view) a self-contained dataset, for example, a business-orientatedarea. An InfoCube is comprised of a set of relational tables arranged according tothe enhanced star schema: a large fact table in the middle surrounded by severaldimension tables.

The data in an InfoCube is stored either physically or in BW Accelerator. TheInfoCube receives the data by means of a data transfer process. It is then availableas an InfoProvider for analysis and reporting purposes.

InfoCubes are made up of a number of InfoObjects. All InfoObjects(characteristics and key figures) are available independent of the InfoCube.Characteristics refer to master data with their attributes and text descriptions.

An InfoCube consists of several InfoObjects and is structured according to theenhanced star schema. This means there is a (large) fact table that contains thekey figures for the InfoCube, as well as several (smaller) dimension tables whichsurround it. The characteristics of the InfoCube are stored in these dimensions.

An InfoCube fact table only contains key figures, in contrast to a DataStoreobject, whose data part can also contain characteristics. The characteristics of anInfoCube are stored in its dimensions.

The dimensions and the fact table are linked to one another using abstractidentification numbers (dimension IDs), which are contained in the key part of therespective database table. As a result, the key figures of the InfoCube relate to thecharacteristics of the dimension. The characteristics determine the granularity (thedegree of detail) at which the key figures are stored in the InfoCube.








Characteristics that logically belong together (for example, district and area belongto the regional dimension) are grouped together in a dimension. By adhering tothis design criterion, dimensions are to a large extent independent of each other,and dimension tables remain small with regards to data volume. This is beneficialin terms of performance. This InfoCube structure is optimized for data analysis.The fact table and dimension tables are both relational database tables.

Figure 51: SAP HANA-Optimized InfoCube

The SAP HANA-optimized InfoCube is a standard InfoCube that is optimizedfor use with SAP HANA. When you create SAP HANA-optimized InfoCubes,you can assign characteristics and key figures to dimensions. The system doesnot create any dimension tables apart from the package dimension however. TheSIDs (master data IDs) are written directly to the fact table. This improves systemperformance when loading data. Since dimensions are omitted, no DIM IDs(dimensions keys) have to be created.

The dimensions are simply used as a sort criterion and provide you with a cleareroverview when creating a query in BEx Query Designer.







Figure 52: SAP HANA-Optimized InfoCube – Tables in the HANA Studio

Hint: A DTP setting is used to automatically activate master data after ithas been updated (for master data load processes). This is possible due tothe fact that aggregates are not used with the SAP HANA database.

You find the structure of the InfoCube in the SAP HANA Studio (or InformationModeler) in the respective catalog for the SAP system, in the folder of the tables.

• Looking at the Active Table reveals the 3 indices which comprise the ActiveTable. Beside the main index with the suffix 00, this is the delta index withthe suffix 70 and the historic index with the suffix 80.

Figure 53: HANA-Optimized InfoCube – Compression








Inventory InfoCubes

Figure 54: Inventory Management (1)

The main processes for the Inventory Management (for non-cumulative keyfigures) has moved to the DTP.

You need the following DTPs to manage inventory data:

• First, the DTP which loads the initial data set. This is indicated via theExtraction Mode of the DTP.

• You need a second DTP for regular movements.

In case you want to load historic data you have to switch on the flag in thisparticular DTP in the productive system.







Figure 55: HANA-Optimized Non-Cumulative InfoCube (1)

Initialization record stored with SID_0RECORDTP = ‘1’ – ‘NCUM Initialization’partition of /BI0/F0IC_C03 table

Historical transactions stored with SID_0RECORDTP = ‘2’ – ‘NCUM History’partition of /BI0/F0IC_C03 table

Delta transactions stored with SID_0RECORDTP = ‘0’ – ‘uncompressed’partition of /BI0/F0IC_C03 table








Figure 56: HANA-Optimized Non-Cumulative InfoCube (2)

Hint: SAP HANA-optimized InfoCubes with non-cumulative key figurescan be integrated as the target of update rules into a 3.x data flow (HANA1.0 SPS05).

Note: A DTP can be changed in a production system if the developmentclass of the imported DTP can be changed. You then just need to changethe settings in the DTP and reactivate it. For more information, see SAPNote 1558791.

This logic replaces the compression logic (and therefore the associated markerupdate) for the SAP HANA-optimized InfoCube. There is no semantic basis forcompression with SAP HANA-optimized InfoCubes. The data is only compiled.Markers are not updated.







Migration

Figure 57: Conversion

If you are using a SAP HANA database, you can only create SAPHANA-optimized InfoCubes. You can continue using existing standard InfoCubesthat do not have the SAP HANA-optimized property or you can convert them.The property Data Persistency in BWA is not available in SAP HANA because theSAP HANA database assumes the role of primary persistence.

Figure 58: HANA-Optimized InfoCube – Conversion of Standard InfoCubes








If you are using a SAP HANA database and want to benefit from it when loadingdata into InfoCubes, we recommend converting existing standard InfoCubes.

Note: Note that the table layout changes during conversion. If you accessdata with programs of your own, you have to adjust these manually afterconversion. We generally recommend only using released interfaces toaccess BW data.

After migration to the SAP HANA database, normal standard InfoCubes arein the SAP HANA database’s column-based store and have a logical index(CalculationScenario). In the analysis, they behave like BWA-indexed InfoCubes.

If the InfoCubes have data persistency in BWA, the content is deleted duringthe system migration to HANA and the InfoCubes are set to inactive. If youwant to continue using one of these InfoCubes as a standard InfoCube, you needto activate it again and reload the data from the former primary persistence(DataStore object for example).

If you have integrated InfoCubes for converting into process chains, there is noneed for you to modify the process chains. Certain process types have becomeobsolete, but can remain in the process chain when a SAP HANA database is used.The obsolete processes do not have any funkction when a SAP HANA database isused. The system simply skips them.

Figure 59: HANA-Optimized InfoCube – Conversion







Procedure

1. There are two ways of calling the conversion transaction:

• You are in the InfoObject editing screen. Choose –Goto– Conversion toSAP HANA-Optimized. The InfoCube you want to edit is displayed.

• Call transaction RSMIGRHANADB directly.2. You can now use input help to select InfoCubes for conversion.3. You can specify whether the log is displayed after conversion.4. Choose Execute. The InfoCubes are converted.

BW Integrated Planning

Figure 60: BW Integrated Planning – PAK Architecture

SAP HANA will be available in multiple deployment options. Phase I is a sideby side approach, where HANA is added to the system landscape and data that isneeded for analytic or other purposes is replicated from the underlying DBMS toHANA using various ELT mechanisms. Phase II is an embedded approach whereHANA replaces the underlying DBMS, for example BW. Phase III is pushingprocessing down into HANA and removing further layers like BW.








Figure 61: SAP HANA and SAP NetWeaver BW

Remodeling: From a technical point of view, no remodeling is required. Theplanning engine has no impact on your existing ABAP-based planning model.

If a planning function is already supported by the planning engine (disaggregationfor example) the planning function will be executed in SAP HANA. If a planningfunction is not supported by the planning engine yet (revaluation for example), theplanning function will be executed in the ABAP stack without HANA support.

Performance optimization: You are advised to investigate the performanceoptimization potential of your current architecture planning architecture. HANAoffers huge performance improvements during runtime. HANA is not able tocompensate in situations where modeling is less than perfect however ☺.

License:

The SAP BusinessObjects Planning and Consolidation, Version for SAPNetWeaver license contains SAP BusinessObjects planning and consolidation,version for SAP NetWeaver (BPC) and the Planning Application Kit. If you needmore details regarding license and pricing, please check our official pricelist.







Figure 62: Planning Applications Kit and SAP HANA

The Planning Applications Kit (PAK) provides a connection between an BW-IPbased planning application and SAP HANA.

It consists of a buffer connector and a function connector which provide a linkto the planning sessions and planning operations that are now located within theHANA database.

Reconfiguration of current planning models is not necessary; existing modelsprofit from significantly increased performance by using PAK.

Figure 63: BW In-Memory Planning: Accelerated Planning Functions








Figure 64: HANA Planning – Simple Disaggregation Example

Figure 65: Deployment Options for BW Integrated Planning

Use of the Planning Applications Kit requires a license for the following SAPfunctionality: ’SAP BusinessObjects Planning and Consolidation, version forSAP NetWeaver’. If you do not have this license, please contact your accountprofessional for further information.







Use of the Planning Applications Kit requires a license for the following SAPfunctionality: ’SAP BusinessObjects Planning and Consolidation, version forSAP NetWeaver’. If you do not have this license, please contact your accountprofessional for further information.

• There are special methods for managing planning sessions commands. Thesemethods handle the interaction between Planning Applications Kit andPlanning Engine.

– Open– Close

• A planning functionality method is also provided for

– Copy– Disaggregate– Set Values– Delta– Restrict– Delete– Lookup– Snapshot– Save– FOX

Figure 66: How To: Customize Planning Application Kit (1)

General activation of the Planning Applications KIT:

SM30: Table view RSPLS_HDB_ACT. Choose HANA_ACT in order to activatethe Planning Applications KIT








Figure 67: How To: Customize Planning Application Kit (2)

Infoprovider specific activation of the Planning Applications KIT:

SM30 Table view: RSPLS_HDB_ACT_IP. To activate Planning Applications KITfor individual Infoprovider in addition. Choose the real-time cube you want touse for HANA planning. This is in order to gurantee a smoth transition fromexisting BW-IP scenarios and to avoid additional roundtrips due to the restrictions(Note 1637199).

Those switches might become obsolete.







Use Cases and Limitations

Figure 68: HANA-Optimized InfoCube








Lesson Summary

You should now be able to:• Understand the motivation for SAP HANA optimized InfoCubes• Identify the difference in the architecture and structure compared with


InfoCubes can be used in







Lesson:70

Semantically Partitioned ObjectLesson Duration: 30 Minutes

Lesson OverviewThis lesson describes when to use the Semantically Partitioned Object (SPO) inmodeling and outlines the use cases, advantages, and limitations of this type ofInfoProvider.


• Describe the use cases of an SPO• Create an SPO and integrate it into the data flow


Business ExampleYou expect a high data volume in the InfoProviders that you provide for reporting.To optimize query performance, you decide to divide the InfoProviders intoseveral semantic partitions.

The Concept of Semantic PartitioningSemantic partitioning means that transactional data is loaded into differentInfoProviders that are partitioned according to characteristics such as:

• Geographical characteristics (countries, regions, and so on)• Time characteristics• Organizational characteristics (departments or business units)

Semantic partitioning is necessary in enterprise data warehouse architecturesbecause it improves performance with mass data and scalability of the datawarehouse. If an InfoCube contains too many records, the compression andreconstruction of aggregates may take a very long time. The same appliesto DataStore objects, where the duration of the activation process increases.Using semantic partitions helps to keep a lower data volume in the respectivePartProviders.







BW362 Lesson: Semantically Partitioned Object

Error handling and the handling of load processes in different time zones is alsofacilitated by this concept. If a request for a region leads to an error, the new datafor the whole InfoProvider would not be available for reporting. With semanticpartitioning, only the data for the affected regions would not be available.PartProviders for regions with different time zones also allow data loading andadministrative tasks to be scheduled independently of the time zone. Withoutpartitioning, it is very difficult to find a suitable time slot for all countries.

Query performance can also be improved by accessing partitioned InfoProviderswith fewer records. This is especially the case if only a particular region or timeinterval that has been used for partitioning is of interest for reporting users.

Implementation of Semantic Partitioning in SAP BWwith Semantically Partitioned ObjectsSemantically Partitioned Objects (SPOs) allow users to create a semantic partitiononce and use it repeatedly. This concept improves scalability and reducesdevelopment efforts when a new partition is created to extend the existing datamodel.

In earlier SAP NetWeaver BW releases, this concept could also be applied, butrequired several manual steps. An administrator of a BW 7.0 system who wantsto partition InfoProviders by geographical characteristics (for example, Europe,North America, and Asia) has to create a master InfoCube and copy it. Afterthat transformations, data transfer processes with different filter settings and –ideally – InfoSources have to be created manually. Changes in the data modelof the InfoCube or changes in the partitioning also have to be applied to theInfoProviders manually.

In SAP NetWeaver BW 7.3, the effort for creating, maintaining, and changingsemantic partitions has decreased significantly. In SAP BW 7.3, a wizard helpsyou to create Semantically Partitioned Objects. These objects comprise multipleInfoCubes or DataStore objects that are logically partitioned. The SPO doesnot bring semantic partitioning as a new concept for data modeling into SAPNetWeaver BW, but makes it easier to implement it by reducing the necessarymanual steps. That means that now only a master InfoCube or master DataStoreobject is required. Multiple InfoCubes or DataStore objects with the samestructure are then created automatically and integrated into the data flow. Changesto the structure do not have to be applied to each object, but can be applied to theSPO once. All data transfer processes (DTPs) for the different partitions can beintegrated into process chains in one step.







The components of the SPO are

• MasterProviderThe InfoProvider that is maintained by the end user and used as a templateobject (InfoCube or DataStore object)

• PartProvidersHomogeneous set of InfoProviders with properties copied from theMasterProvider. An SPO partition is characterized by partitioning criteria(maximum 5 characteristics) that have to be disjoint across SPO partitions(no overlap).

• InfoSourcesUsed as interface objects to embed the SPO in the data flow

An SPO is always created with two InfoSources: one for incoming and onefor outgoing data flows. The InfoSources have the function of an inboundand outbound data layer for the object, which facilitates the integration of theSemantically Partitioned Object into a data flow. Between the InfoSources andthe partitions there are simple dummy transformations. Actual transformation ofdata takes place in the transformation objects underneath or above the inboundand outbound InfoSources. Note that reporting is only possible on the partitions,not on the SPO itself.







BW362 Lesson: Semantically Partitioned Object

Lesson Summary

You should now be able to:• Describe the use cases of an SPO• Create an SPO and integrate it into the data flow






Unit Summary BW362

Unit SummaryYou should now be able to:• Explain the motiviation for HANA optimized DataStore Objects• Identify the difference in the architecture and structure compared with


Objects can be used in• Understand the motivation for SAP HANA optimized InfoCubes• Identify the difference in the architecture and structure compared with


InfoCubes can be used in• Describe the use cases of an SPO• Create an SPO and integrate it into the data flow







Unit 375 Consuming HANA Models in BW

Unit OverviewContent of this unit is Consuming HANA Models in BW


• Understand the Architecture when consuming SAP HANA models in SAPBW

• Show how SAP HANA models can be accessed from SAP BW for queryusage (TransientProvider)

• Merge the SAP BW and SAP HANA models via a CompositeProvider• Include SAP HANA data via DB Connect in SAP BW Staging process

Unit ContentsLesson: VirtualProvider .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78Lesson: TransientProvider.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84Lesson: CompositeProvider .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91Lesson: DB Connect .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .102






Unit 3: Consuming HANA Models in BW BW362

Lesson:76

VirtualProviderLesson Duration: 5 Minutes

Lesson OverviewContent of this lesson is VirtualProvider


• Understand the Architecture when consuming SAP HANA models in SAPBW

Business Example

Architecture

Figure 69: Overview: Mixed Scenarios SAP BW & SAP HANA Schemas

TransientProvider based on HANA Model







BW362 Lesson: VirtualProvider

For ad hoc scenariosGenerated not modeled, no InfoObjects requiredFull BEx Query supportCan be included in a CompositeProvider to combine with other BWInfoProviders

VirtualProvider based on HANA Model

For a flexible integration of HANA data with BW managed metadata (e.g.lifecycle)Security handled by BWFull BEx Query supportCan be included to Composite- and MultiProvider to combine with otherBW InfoProviders

Semantically Partitioned Object

Figure 70: Semantically Partitioned Object – Modeling for Large Data Volume(DSO or InfoCube)

A semantically partitioned object is an InfoProvider that consists of severalInfoCubes or DataStore objects with the same structure. Semantic partitioningis a property of the InfoProvider. You specify this property when creating theInfoProvider. Semantic partitioning divides the InfoProvider into several small,equally sized units (partitions).







A semantically partitioned object offers the following advantages compared tostandard InfoCubes or standard DataStore objects:

• Better performance with mass data: The larger the data volume, the longerthe runtimes required for standard DataStore objects and standard InfoCubes.Semantic partitioning means that the data sets are distributed over severaldata containers. This means that runtimes are kept short even if the datavolume is large.

• Close data connection: Error handling is better. If a request for a region endswith an error, for example, the entire InfoProvider is unavailable for analysisand reporting. With a semantically partitioned object, the separation of theregions into different partitions means that only the region that caused theerror is unavailable for data analysis.

• Working with different time zones: EDW scenarios usually involve severaltime zones. With a semantically partitioned object, the time zones canbe separated by the partitions. Data loading and administrative tasks cantherefore be scheduled independently of the time zone.

VirtualProvider

Figure 71: VirtualProvider Based on SAP HANA

Virtual Provider is a type of InfoProvider which reads data from a BW Infocube.Characteristics and Key figures are created based on the data fields in the HANAmodel and an Infocube is constructed using the characteristics as dimension andkey figures duly filled in.








The advantage of the Virtual provider over Transient provider is that here theInfocube acts as Dataprovider and it can be extended to have BW traditionaldatatype as its source and which help in multi-level reporting.

For example: If data comes as a timestamp from the HANA model, you canactually inherit the traditional date datatype from BW and the data could bedisplayed in terms of quarter, year, calendar week etc., and it eventually shows theflexibility you have over reporting when you use Virtual Provider.

Creating VirtualProviders Based on a SAP HANA Model

You can create a VirtualProvider based on a SAP HANA model if you want to usethis model in the BW system. This VirtualProvider can be used in a MultiProvider.Navigation attributes can be used, and the BW analysis authorizations apply.

Prerequisites

You are using a SAP HANA database. You have created a SAP HANA modelin SAP HANA Studio.

Procedure

In the Data Warehousing Workbench under Modeling, select the InfoProvider tree.In the context menu, choose Create VirtualProvider.

Select Based on a SAP HANA Model.

Choose Details. In the dialog box, enter the SAP HANA model and the packagethat it belongs to. Press (Continue).

Choose (Create). The VirtualProvider processing screen appears.

Define the VirtualProvider by adding the required InfoObjects. To do this, youneed to know how the SAP HANA model is defined.

Choose Provider-Specific InfoObject Properties from the context menu on theDimensions and Key Figures folders. In the following dialog box, you can assignthe InfoObjects to the fields in the SAP HANA model. Press (Continue).

Activate the VirtualProvider.

Hint: Masterdata also possible as a VirtualProvider

Using Virtual Master Data

If you want to use virtual navigation attributes and texts in a VirtualProvider basedon an SAP HANA model, you need to create virtual master data.

Prerequisites You are using an SAP HANA database.

Procedure: You are in the Data Warehousing Workbench in the Modeling area.Choose the InfoObjects area.







In the context menu for your InfoObjectCatalog, choose Create InfoObject.Assign a name and a description and choose (Continue). The InfoObject editingscreen appears.

Make the required entries for your InfoObject. On the Master Data/Texts tabpage, choose SAP HANA Attribute View as the master data access. Specify anSAP HANA package and an SAP HANA attribute view. Choose Suggest SAPHANA Links.

Select the SAP HANA attributes for which you want to generate proposals andchoose (Apply). A list of proposals appears. The attributes of the SAP HANAmodel are displayed in folders. The proposals are listed under these folders.Choose (Technical Details) to display the strategy for creating proposals.

In each case, select a suitable proposal for attributes, texts, and compounding (ifapplicable). If none of the suggested InfoObjects are suitable, you can initiallyleave the attribute unassigned and assign it manually later on. Choose (Continue).The attributes are assigned. If you have selected texts (TXTSH, TXTMD,TXTLG), the relevant indicator for texts is set on the Master Data/Texts tab page.Assigning attributes manually: Choose Maintain HANA Links.

In each case, select suitable SAP HANA attributes for attributes, texts, andcompounding (if applicable) and choose (Apply). Activate the characteristic.Result You can now use the characteristic with virtual master data in yourVirtualProvider.








Lesson Summary

You should now be able to:• Understand the Architecture when consuming SAP HANA models in SAP

BW







Lesson:82

TransientProviderLesson Duration: 5 Minutes

Lesson OverviewContent of this lesson is TransientProvider


• Show how SAP HANA models can be accessed from SAP BW for queryusage (TransientProvider)

Business Example

TransientProviders

Figure 72: Analytical Index – TransientProvider







BW362 Lesson: TransientProvider

If you want to use SAP BW OLAP functions to report on SAP HANA Analyticor Calculation Views you can publish these SAP HANA models to the SAP BWsystem.

Publish Analytic/Calculation View: Transaction RSDD_HM_PUBLISH Thesepublished Analytic or Calculation Views are visible as Analytical Indexes(TransientProviders)

Administration of Analytical Indexes: Transaction RSDD_LTIP

Note: Transient Provider are not transportable at the moment and mustre-created in all systems.

1. Run transaction RSDD_HM_PUBLISH2. Choose an SAP HANA Model belonging to a catalogue (SAP HANA

package)3. Choose Create4. The system suggests a name for the new Analytical Index from the SAP

HANA Model‘s name. You can change this name. Choose Enter. Thedefinition of the Analytical Index is displayed.

5. On the tab Properties you can assign an InfoArea to the Analytical Index.6. On the tabs Characteristics and Key Figures you can assign SAP BW

InfoObjects to the fields of the Analytical Index. Thus, the Analytical Indexhas access to SAP BW meta data. Furthermore, analysis authorizations forthese InfoObjects are considered.

7. Choose Save. The Analytical Index is created

• Generated name for TransientProvider: @3 .........

RESULT: SAP BW Queries accessing the Analytical Index can be definednow!







Figure 73: Publishing SAP HANA Models: Step 1

Figure 74: Publishing SAP HANA Models: Steps 2-4

Restrictions for HanaModels in BW

ProviderName

Limitation to catalog_name+cube_name+schema not longer than 63 (Trex APIlimitation)








The full model name incl. package must be <= 55 – this is because thecolumn view must be <= 64 and the name of it for the ABAP API is_SYS_BIC:<package>/<name>.

Providername is as follows: @3 + (catalog_name+_+cube_name)/alias

ColumnNames

The column names must be upper case and <= 64 including suffixes .descriptionand .currency. I.e. an attribute with a description must be <= 52 and a measurewith a currency conversion <= 55.

BW might use alias in the most cases

Infobject name is build as follows: Providername + @ + column_name/Alias

Upper-case








Figure 78: Reporting on Analytical Index (1)

Figure 79: Reporting on Analytical Index (2)







Lesson Summary

You should now be able to:• Show how SAP HANA models can be accessed from SAP BW for query

usage (TransientProvider)







BW362 Lesson: CompositeProvider

Lesson:89

CompositeProviderLesson Duration: 10 Minutes

Lesson OverviewContent of this lesson is CompositeProvider


• Merge the SAP BW and SAP HANA models via a CompositeProvider

Business Example

CompositeProviders

Hint: Since BW 7.3 SP08 CompositeProviders are integrated into theData Warehousing Workbench







Figure 80: Composite Provider

Flexible modeling with no data persistency

• Rapid prototyping• Ad-hoc scenarios• BW Workspaces (BW InfoProviders with local files)

CompositeProvider – new with BW 7.3

• Combine InfoProviders (InfoCubes, DataStore Objects) and AnalyticIndexes via UNION, INNER JOIN and LEFT OUTER JOIN

• Can only be used in combination with BW powered by SAP HANA (andpartially with BW Accelerator)

• NION and JOIN operations are executed in HANA DB and not theapplication server – if possible from a data consistency point of view withoutjoin column information

• Exposed as standard BW InfoProvider for BI Client consumption (BEx,BI tools)

• Transaction: RSLIMOBW

Creating CompositeProviders

A CompositeProvider is an InfoProvider, which combines data from severalanalytic indexes or from other InfoProviders (by Join or Union), and makes thisdata available for reporting and analysis. The CompositeProvider is defined in agraphical environment, thus faciilitating rapid modeling. This makes it possible to








bring together data from multiple sources using analytic indexes and to quicklyput together a prototype. Storing the data in BW Accelerator or in SAP HANAalso ensures faster access to data in the query.

(1) Creating CompositeProviders from Analytical Indexes and from otherInfoProviders

1. Call transaction RSLIMOBW.2. Enter a name for your CompositeProvider. The maximum length of the name

is 10 characters. The system adds the prefix @3 to the InfoProvider name.3. Choose Create. The graphical modeling environment appears.4. You can drag and drop the required analytic indexes (from the tree on the left

of the screen) onto the modeling area. Choose Provider Display to view theother available InfoProviders.

5. Proceed as described above, starting with step 5.

Note: Unlike the CompositeProvider that you create using transactionRSLIMO, you can transport the CompositeProvider from transactionRSLIMOBW.

Prerequisite for transporting:

• The CompositeProvider does not contain an analytic index.• The InfoProviders that make up the CompositeProvider are already

available in the production system.• You have installed the R3TRANS version, released on 5th September

2011 (720-R3TRANS-Patch).• You have installed the SAP Note 1643629.







Figure 81: Creating a CompositeProvider: Procedure (1)

Figure 82: Creating a CompositeProvider: Step 1








Figure 83: Creating a CompositeProvider: Steps 2-3

Figure 84: Creating a CompositeProvider: Steps 4-5







Figure 85: Creating a CompositeProvider: Steps 6









Figure 91: Reporting on CompositeProvider

Figure 92: Reporting on CompositeProvider







Figure 93: Creating a CompositeProvider: Using Constant Values

Figure 94: Ad-Hoc Reporting with SBO Analysis for Microsoft Excel








Lesson Summary

You should now be able to:• Merge the SAP BW and SAP HANA models via a CompositeProvider







Lesson:100

DB ConnectLesson Duration: 10 Minutes

Lesson OverviewContent of this lesson is DB Connect


• Include SAP HANA data via DB Connect in SAP BW Staging process

Business Example

DB Connect to Replicate Data

Figure 95: DB Connect Architecture







BW362 Lesson: DB Connect

Using the functionality Multiconnect you can open further DataBase connectionsand access these external DataBases via these DB connections.

The DB connections can be used as source systems for SAP BW. DB Connectenables the data transfer from external DataBase tables and views into SAP BW.

General Prerequisites: Installation of DB specific DB Client and Installation ofDB specific DBSL on the SAP BW application server. In case of HANA: SAPHANA DBSL installation is necessary.

Figure 96: SAP HANA Data for SAP BW Staging – Example

Figure 97: Supported Databases







In general, BW application servers can only be supported on the operating systemwhere a SAP Database Shared Library (DBSL) has been released for the BWdatabase and the source database.

Database Table as a Destination Type

You can select DB Table as a destination type.

Features

Generating Database Tables

When you activate the open hub destination, the system generates a database table.The generated database table has the prefix /BIC/OHxxx (xxx is the technicalname of the destination).

Deleting Data from the Table

With an extraction to a database table, you can either retain the history of thedata or just store the new data in the table. Choose Delete Data from Table whendefining your destination if you want to overwrite the fields. In this case, the tableis completely deleted and regenerated before each extraction takes place. Werecommend that you use this mode if you do not want to store the history of thedata in the table. If you do not select this option, the system only generates thetable once before the first extraction. We recommend using this mode if you wantto retain the history of the extracted data. Note that the table is always deletedand regenerated if changes are made to the properties of the database table (byadding fields for example).

Table Key Fields

You can choose whether to use a technical key or a semantic key.

Technical key:

If you set the Technical Key indicator, a unique key is added that consists of thetechnical fields OHREQUID (open hub request SID), DATAPAKID (data packageID), and RECORD (sequential number of a data record to be added to the tablewithin a data package). These fields display the individual key fields for the table.Using a technical key with a target table is particularly useful if you want to extractdata to a table that is not deleted before extraction. If an extracted record has thesame key as a record that already exists, the duplicate records cause a short dump.

Semantic key:

If you set the Semantic Key flag, the system selects all fields in the field list assemantic keys. You can change this selection in the field list. Note howeverthat using a semantic key can result in duplicate records. The records are notaggregated. Instead each extracted record is saved in the table.

Writing Data Directly to a Different SAP HANA Database








If you specify a previously created connection to a SAP HANA database for DBConnection Name, the data (together with the generated table) is written to theSAP HANA database.

Hint: Other databases are not supported here. Only the SAP HANAdatabase is supported.

Figure 98: DB Connect Setup: Procedure I







Figure 99: DB Connect Setup: Procedure II

In the BW On HANA Scenario ,we would create a DB Connect with the HANADatabaseand then create datasources on the HANA Tables accessed in theAnalytical/Calculation Views to extract the data.

Figure 100: DB Connect DataSources: Procedure I








Figure 101: DB Connect DataSources: Procedure II

Figure 102: DB Connect DataSources: Procedure III







Figure 103: DB Connect DataSources: Procedure IV

Figure 104: DB Connect DataSources: Procedure V








Figure 105: DB Connect DataSources: Procedure VI

Then an InfoPackage would be built on the datasource to load the data to the PSAand then via transformation we load the data to the Infocubes and build querieson them for reporting.

Figure 106: DB Connect DataSources: Execute Preview







Further Integration Aspects

Figure 107: Direct loading of HANA data into BW

Optimized SAP HANA Data Load into SAP NetWeaver BW

• Complementary to DB Connect• Based on new source system type: Operational Data Provider (ODP) with

the context ‘HANA’• Enable direct loading from HANA Views via DTP into BW managed schema• Data persistency in PSA optional Mass data loading

You can use the Operational Data Provisioning Framework (ODP) to transferdata sources from certain SAP repositories to BW. The following SAPrepositories are currently supported:

• SAP HANA Database (that an ABAP system is running on)• SAP Business ByDesign: More information








Operational Data Provisioning offers the following communication channels fordata transfer:

• Remote Function Call (RFC): You can use RFC to access ABAP systemsthat run on a SAP HANA database in order to transfer data from SAP HANAviews to BW.

• Web Service (SOAP via HTTP or HTTPS): The Web Service implementationcan occur outside of ABAP. You can use Web Service to access SAP BusinessByDesign systems. The data in the source is available for extraction in theform of operational data providers. An operational data provider definesinterfaces for transaction data and master data (attributes, texts, hierarchies).Once implemented for SAP HANA and SAP Business ByDesign, theseinterfaces make it possible to access data for replication to BW.

Process

1. You create an ODP source system to connect the source of the data transfer, aSAP HANA database or a SAP Business ByDesign system for example, tothe BW system with.

2. You create a DataSource for an operational data provider belonging to thesource.

Result You can now load the data to the persistent staging area (PSA) in BW usingan InfoPackage and then load it into an InfoProvider or load it directly into anInfoProvider using a data transfer process.

Authorizations

In the SAP HANA database, analytic privileges are used to define which users areallowed to view which data records for analysis purposes. Analytic privileges arepersisted on the BW system and in the SAP HANA database.

To access a view in SAP HANA, this user requires the corresponding analyticprivileges and the authorizations for the corresponding schema. In the BWsystem (ABAP), the access by the user performing the extraction is controlledusing authorization object S_RS_ODP_H. The authorization object can controlaccess to SAP HANA package level and to the view level. We recommend usingthe authorization object. If the user performing the extraction does not haveauthorization object S_RS_ODP_H in his/her profile however, s/he can stillperfrom the extraction if there is a user with the same name with the requiredanalytic privileges in SAP HANA.

To analyze the data replicated into BW, the user executing the query requires thecorresponding analysis authorizations. You can find out more about defining andassigning analysis authorizations under Analysis Authorizations.

Direct Load to InfoProvider







In the data transfer process (DTP) maintenance screen, you can specify thatdata is not extracted from the Persistent Staging Area (PSA) of the DataSource.Instead the data is requested directly from the data source at DTP runtime andthen transferred to the InfoProvider. It is not necessary to load the data into thePSA beforehand, using an InfoPackage.

The flag Do not extract from PSA; use direct access to data source is displayedif the DTP source is a DataSource and the source system is an operational dataprovisioning (ODP) source system. Using the ODP data replication interface andthis function allow you to extract mass data.

Note the following:

• Direct loading in Full mode is supported for the ODP contexts SAP HANAand SAP Business ByDesign.

• If errors occur during processing, you need to extract the data again in BWbecause the PSA is not available in the buffer.








Figure 108: Easy Consumption of HANA Master Data in BW Queries

SAP NetWeaver BW Virtual Master Data

• HANA attribute view exposed as master data in BW• No data staging of SAP HANA master data required• Prior to SP 8 information in master data tables stored in SAP HANA schema

could only be consumed in BW query via staging into BW

Figure 109: Flexible BW Data Provisioning for SAP HANA Applications







Using Virtual Master Data

If you want to use virtual navigation attributes and texts in a VirtualProvider basedon an SAP HANA model, you need to create virtual master data.

Prerequisites

You are using an SAP HANA database.

Procedure

1. You are in the Data Warehousing Workbench in the Modeling area. Choosethe InfoObjects area.

2. In the context menu for your InfoObjectCatalog, choose Create InfoObject.Assign a name and a description and choose (Continue). The InfoObjectediting screen appears.

3. Make the required entries for your InfoObject.4. On the Master Data/Texts tab page, choose SAP HANA Attribute View as

the master data access.5. Specify an SAP HANA package and an SAP HANA attribute view.6. Choose Suggest SAP HANA Links.7. Select the SAP HANA attributes for which you want to generate proposals

and choose (Apply). A list of proposals appears. The attributes of the SAPHANA model are displayed in folders. The proposals are listed under thesefolders. Choose (Technical Details) to display the strategy for creatingproposals.

8. In each case, select a suitable proposal for attributes, texts, and compounding(if applicable). If none of the suggested InfoObjects are suitable, you caninitially leave the attribute unassigned and assign it manually later on.Choose (Continue). The attributes are assigned. If you have selected texts(TXTSH, TXTMD, TXTLG), the relevant indicator for texts is set on theMaster Data/Texts tab page.

9. Assigning attributes manually: Choose Maintain HANA Links.10. In each case, select suitable SAP HANA attributes for attributes, texts, and

compounding (if applicable) and choose (Apply).11. Activate the characteristic.

Result

You can now use the characteristic with virtual master data in your VirtualProvider








Open Hub Destination with new target SAP HANA DB

• Support data transfer from BW InfoProviders, DataSources and Queries intotables residing in SAP HANA for further usage by HANA applications

• Default is 1:1 mapping, individual transformation can be modeled• Delta extraction supported for InfoProviders and DataSource• Query snapshots via QueryProvider are possible• Supported also for BW on classic RDBMS

Figure 110: Easy BW InfoProvider Consumption

Generate Analytic View for BW InfoProvider via HANA Modeler

• Generated Analytic View contains basic BW Metadata• Generated Analytic View can be consumed via SAP HANA interfaces and

used in further SAP HANA models• This enables SAP BO Explorer and SAP Visual Intelligence on BW data

Explorer on BW on HANA is based on a new architecture: Explorer on BWon HANA leverages HANA’s own repository, its modeling capabilities andsecurity model. HANA views are created directly on the underlying tables ofBW InfoProvider as BW sits on HANA. The design is based on metadata of BWInfoProviders.







The major difference between “Explorer, accelerated (with BWA)” and“BW/HANA Explorer” is, that HANA has its own modeling environment(BWA/Explorer has not). The HANA modeling tool is aware of the capabilities ofthe HANA engine and is enhanced as the engine capabilities advance.

Explorer integration for BW on HANA is based on the BW model & HANAmodel interoperability.

BWA

• Data: Data needs to be materialized in BWA• Additional data materialized specifically for Explorer• Text available in only one language• Modeling: BWA has no modeling tools• Model lifecycle managed by BW• Security: No BWA-own security mechanism• BW security hard-coded into indexes• Security lifecycle managed by BW

BW-HANA

• Data: Non-materialized HANA views• Multilingual text supported• Modeling: Automated generation of HANA Models based on BW models

via HANA Studio Models are managed and extended via HANA modeler• (In Future: BW models will automatically provide a BW managed HANA

model)• Security: Leverage native HANA security infrastructure• HANA privileges will be generated based on BW authorizations• Only for HANA optimized InfoCubes and DSO objects

Hint: Please noticed SAP note 1769374 (Correction incl. BW SP09)and note 1764251 (Documentation).

Prerequisites – Limitations

• SAP HANA 1.0 SP04 Rev37• SAP Privileges (BW schema to import)• Calculated Key Figures and Restricted Key Figures need to be re-created

in calculation views• Reporting: InfoCube generated calculation views and DSO generated

analytical views








Analysis Authorization

• If 0TCAIPROV included the authorization moved to HANA → AnalyticalPrivileges

• Other BW authorizations are not considered

Hint: Changes in BW are not automatically reflected to HANA andre-import of BW modells → Overwrite changes in HANA







Lesson Summary

You should now be able to:• Include SAP HANA data via DB Connect in SAP BW Staging process







BW362 Unit Summary

Unit SummaryYou should now be able to:• Understand the Architecture when consuming SAP HANA models in SAP

BW• Show how SAP HANA models can be accessed from SAP BW for query

usage (TransientProvider)• Merge the SAP BW and SAP HANA models via a CompositeProvider• Include SAP HANA data via DB Connect in SAP BW Staging process






Unit Summary BW362







Unit 4117 BI for BW powered by HANA

Unit OverviewContent of this unit is BI for BW powered by HANA


• Rephrase basics in BI for BW on HANA

Unit ContentsLesson: BI for BW Powered by HANA ... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .122






Unit 4: BI for BW powered by HANA BW362

Lesson:118

BI for BW Powered by HANALesson Duration: 15 Minutes

Lesson OverviewBI for BW Powered by HANA


• Rephrase basics in BI for BW on HANA


Business Example[Enter a business example that helps the learner understand the practical businessuse of this lesson.]

Figure 111: Connectivity SAP BW and SAP BI







BW362 Lesson: BI for BW Powered by HANA

Figure 112: Crystal Reports for Enterprise

SAP Crystal Reports, the de facto standard for enterprise reporting, enablesorganizations to deliver easy-to-consume, pixel-perfect, personalized documentswith guided interactivity. Examples of these documents include external-facingcommunications such as invoices and bank statements and internal operationaldocuments such as commission reports and HR reports. It offers a powerfuldesign environment to build visually compelling reports without compromisingproductivity.

Figure 113: Dashboards (Xcelcius)







SAP BusinessObjects Dashboards is a drag-and-drop visualization tool to createinteractive analytics that can be turned into powerful, personalized dashboards.Drop-down menus and sliders allow you to present complex business data clearly,giving decision makers an easy way to interact with data and test out businessscenarios – all with the click of a mouse.

Figure 114: Web Intelligence

SAP BusinessObjects Web Intelligence offers business users self-service access todata, ad-hoc reporting, and intuitive interactive analysis, all in a single solution.Business users get answers to their spontaneous and iterative business questionsand can turn data into business insights and share those insights across theirorganization.








Figure 115: Analysis, Edition for Microsoft Office

SAP BusinessObjects Analysis, edition for Microsoft Office, empowers businessanalysts to perform advanced analysis of data residing in SAP NetWeaver BWthrough an intuitive user interface directly within their familiar Microsoft Officeenvironment.

Figure 116: Analysis, Edition for OLAP







SAP BusinessObjects Analysis, edition for OLAP, empowers business analyststo perform analysis of multidimensional data through an intuitive Web interfacethat delivers a full range of analytical functions. Analysts can quickly answersophisticated business questions and then share their analysis workspace withothers, spreading knowledge beyond the confines of a single department or group.

Figure 117: Explorer

For example,

SAP BusinessObjects Explorer is used by Molson Coors managers and analyststo access real-time production, supply chain, and sales data in order to meetchallenges of the beer business, a perishable, price-sensitive product (beverage).SAP BusinessObjects Explorer allows the managers to manage inventory levelsmore effectively and avoid stock outs, and the ability to validate market sharemore rapidly (from 1 day to 30 minutes).

SAP BusinessObjects Explorer








Starting with a search, and moving on to a highly-intuitive interface, users “walk”through the data, guided by the product, to answer questions and gain insight.

• By analyzing your existing SAP BI infrastructure (“universes” for those ofyou familiar with the term), Explorer understands the “shape” of the dataand suggests paths through it, based on dependencies and relationships. Itknows, for example, that wine is classified by color before grape, that carsare classified by engine size, and so on.

• Explorer also adapts its visualization techniques based on the informationbeing viewed, dynamically choosing between pie charts, bar charts, bubblecharts, and other visualization possibilities.

• The majority of decision makers believe they do not have all the informationneeded to make good decisions. Casual business users are not served byexisting traditional BI tools, though they need access to corporate data to dotheir jobs efficiently and to make informed decisions.

– They are not power users or analysts who work on the data on a dailybasis.

– They dont run queries like other SAP BI users; they probably dontunderstand the data structures.

– BI tools available today do not serve their needs as they typicallyrequire training, understanding of analytical methods etc.

Figure 118: Launch Pad

The Business Intelligence launch pad allows users to find, access, manage andwork with BI efficiently and securely.







From BI launch pad, you can access Crystal reports, Web Intelligence documents,and other objects, and organize them to suit your preferences.

You can view information in your web browser, export it to other businessapplications (such as Microsoft Excel), and save it to a specified location.

SAP BusinessObjects Enterprise also provides access to a range of analytic toolsto help you explore information in more detail.Up and running out of the box








Lesson Summary

You should now be able to:• Rephrase basics in BI for BW on HANA






Unit Summary BW362

Unit SummaryYou should now be able to:• Rephrase basics in BI for BW on HANA







Unit 5127 SAP BW Workspace

Unit OverviewContent of this unit is SAP BW Workspace


• Leverage SAP BW Workspace

Unit ContentsLesson: SAP BW Workspace ... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .132






Unit 5: SAP BW Workspace BW362

Lesson:128

SAP BW WorkspaceLesson Duration: 15 Minutes

Lesson OverviewBW Workspace


• Leverage SAP BW Workspace


Business Example

Figure 119: BW Workspaces Introduction

SAP NetWeaver BW contains various functions that enable you to create ad-hocscenarios for rapid prototyping. These functions are available in a BW workspacefor users in specialist departments. Users can create ad-hoc scenarios in anenvironment specifically designed for these users. The environment is integratedinto the existing BW landscape but also makes BW functions less complex.







BW362 Lesson: SAP BW Workspace

A BW workspace is a special area, where new models can be created based oncentral data from the BW system and local data. Workspaces can be managed andcontrolled by a central IT department and used by local special departments. Thismeans you can quickly adjust to new and changing requirements. The aim ofworkspaces is to bridge the gap between the central requirements and the flexibilityrequired locally. Central architected data marts from the IT department can becombined, in a workspace, with data marts from the specialized departments.

BW workspaces consist of an administrator tool, workspaces administration andthe Workspace Designer – a Web-based working environment for business users.

• Creating and monitoring workspaces.• Making indexed InfoProviders from the BW system available in the

workspaces.• Assigning authorizations for workspaces and data from the BW system.

The administrator has the following tasks to perform for workspace administration:

• The business user can do the following in Workspace Designer• Upload his/her own data• Create new data models based on their own data and InfoProviders. Create

queries.

Figure 120: BW Workspace Tasks

A workspace has to be created by an administrator before a user can work in it.The administrator defines settings such as lifetime, maximum disk space and theBW InfoProviders available in the workspace.

Call Workspace Administration from your user menu. You can use this to editeither just one individual workspace (transaction RSWSP) or to edit severalworkspaces via a structure (transaction RSWSPW).







Figure 121: BW Workspace Configuration

Figure 122: BW Workspace Administration 1

A workspace has to be created by an administrator before a user can work in it.The administrator defines settings such as lifetime, maximum disk space and theBW InfoProviders available in the workspace.

Procedure








Call Workspace Administration from your user menu. You can use this to editeither just one individual workspace (transaction RSWSP) or to edit severalworkspaces via a structure (transaction RSWSPW).

Editing Individual Workspaces

Select a workspace to edit or enter a name for a new workspace and choose Create.

Editing Multiple Workspaces

The folder <ROOT> is initial. You can create your own folders for yourworkspaces below this. You can also upload a folder structure from a CSV file.More information: Managing the Folder Structure.

Choose a workspace to edit or create a new one by choosing Create Workspace inthe context menu for your folder.

Tab: Settings

You can make settings to define how the workspace is used:

General Settings:

You can set an expiry date. Upon expiry, the workspace is no longer available inWorkspace Designer. Following consultation with the user, the administratorcan extend the validity of the workspace or delete it, together with the objects itcontains.

You can set a prefix for the providers in the workspace. All providers and transientqueires in the workspace are then given this prefix. This prefix cannot be changedonce an object hast been created with it.

You can enter the name of two contacts who can be called upon if problems arisewith the workspaces.

Settings for Central Providers:

You can assign a MultiProvider to the workspace. This is then assigned as acentral provider. You need to explicitly select the InfoProviders you need fromthe MultiProvider on the Central Providers tab page. More information: TheAssigned MultiProvider

Settings for Local Providers:

You can set the maximum memory space for your own data in the workspace andthe maximum number of providers. One provider is created for each uploadeddata source. The system also displays the used memory and the number ofproviders created.

If you select Data Backup, a backup will be made of the uploaded data on the BWdatabase as well as in the BWA. More information: Activating Data Backupsfor Local Providers

Settings for CompositeProviders:






http://help.sap.com/saphelp_nw73/helpdata/en/cf/0ee9899daa4eb786e8a7f60ac9a540/content.htm

http://help.sap.com/saphelp_nw73/helpdata/en/3e/06b5977f6344899ed93f0f2231c9de/content.htm

http://help.sap.com/saphelp_nw73/helpdata/en/3e/06b5977f6344899ed93f0f2231c9de/content.htm

http://help.sap.com/saphelp_nw73/helpdata/en/af/a2cf7f6cfe40329410dcf294b5198e/content.htm

http://help.sap.com/saphelp_nw73/helpdata/en/af/a2cf7f6cfe40329410dcf294b5198e/content.htm


Under certain circumstances, uploading local data can cause new master dataattributes to be created when a query is created. The Creation of Master DataAllowed flag allows you decide whether or not this should happen.

If you set the Non-Unique Join Columns Allowed flag, a multiplication of keyfigures can occur if join links are used when modeling a CompositeProvider. Forinformation about key figure multiplication, see: Union / Inner Join / Left OuterJoin.

If you set the Key Figure Copying Allowed flag, you can copy calculated andrestricted key figures, which have been defined for the individual InfoProviders ofa CompositeProvider as the global key figures for the CompositeProvider.

Tab Page: Central Providers

You can drag indexed BW InfoProviders that are in-memory (BWA: BWA-indexedas secondary persistence; SAP HANA as primary persistence) from the objectrepository on the left to the right.

Note: If you subsequently call a workspace with central providers thathave already been assigned, the object tree is not displayed automatically.You have to choose (Build InfoProvider Selection) for this to happen.

You can also select DataSources that can be used in BW Workspace Designer asthe source for creating a local provider. To select DataSources, choose (DisplayDataSource Selection). For DataSources of type File, the system checks whetherthe file is located on the application server. If not, it cannot be selected.

Note: Using DataSources in BW Workspaces is not recommended formass data.

The InfoProviders that you drag to the right are assigned to the workspace and canthen be used in Workspace Designer for modeling CompositeProviders.

The DataSources that you drag to the right serve as the source for uploads to alocal provider that can be used for modeling.

By double-clicking on an InfoProvider, you can display it.

For InfoCubes from assigned MultiProviders, you can define whether they can beused for the workspace.

You can also define whether certain key figures or characteristics can be usedfor the workspace.

Tab Page: Local Providers

If data has already been uploaded in Workspace Designer, you see a list of localproviders created during the upload. The system displays the status for each localprovider. OK, With Errors, Inactive or Analytic index does not exist. You canremove workspace assignments from the list for analytic indexes that no longerexist. By choosing (Check) you can run a more detailed analysis of the status.







http://help.sap.com/saphelp_nw73/helpdata/en/5e/13a3d8fd42487ea5adee7d9379c34f/content.htm



These local providers are edited in Workspace Designer. There is also a transactionthat provides you with an overview of the local providers (analytic indexes) thatyou can use. More information: Managing Analytic Indexes.

You can also restore the analytic indexes if they are backed up in the BW system(if you are using a BWA). Choose (Restore).

Note: If data backup is activated, your models and data that you haveuploaded are also restored during a complete restore of BWA indexesbelonging to a BW system. In BW Accelerator Monitor (transactionRSDDBIAMON), you can use the Rebuild BWA Indexes function.

Tab Page: CompositeProviders

The system displays a list of the CompositeProviders that have been created inWorkspace Designer. The system displays the status for each CompositeProvider.OK, With Errors, Inactive or CompositeProvider does not exist.

You can remove workspace assignments from the list for CompositeProvidersthat no longer exist.

Tab: Users

The system displays a list of users who are authorized to work or runworkspace-specific queries in the workspace in question. The authorizations arechecked using the assigned roles/profiles in the user master record. The variousauthorizations (Workspace Designer/query) are displayed in the list using flags.

Note: Note however that the list can only contain users that you areauthorized to display user master record maintenance for.

Finish Editing the Workspace

Check the workspace. During the check, the system checks the active and revisedversion if one exists.

Note: There are two versions of the check if you have already activatedthe workspace (active version), made another change and only saved it forthe time being (revised version).

Save and activate the workspace. You can only use activated workspaces inWorkspace Designer.








Enhancement Spot for BW Workspaces

Enhancement spot RSL_WORKSPACE for BW Workspaces provides you withtwo BAdIs:

RSL_WORKSPACE_DESIGNER_BADI: Enhancements in BWWorkspaceDesignerYou can learn how these are used by taking a look at the exampleimplementations

For more general information about using Business Add-Ins (BAdIs), see BusinessAdd-Ins (BAdIs)








http://help.sap.com/saphelp_nw73/helpdata/en/8f/f2e540f8648431e10000000a1550b0/frameset.htm

http://help.sap.com/saphelp_nw73/helpdata/en/8f/f2e540f8648431e10000000a1550b0/frameset.htm


You can drag indexed BW InfoProviders that are in-memory (BWA: BWA-indexedas secondary persistence; SAP HANA as primary persistence) from the objectrepository on the left to the right.

Hint: If you subsequently call a workspace with central providers thathave already been assigned, the object tree is not displayed automatically.You have to choose the icon (Build InfoProvider Selection) for this tohappen.

You can also select DataSources that can be used in BW Workspace Designer asthe source for creating a local provider. To select DataSources, choose (DisplayDataSource Selection). For DataSources of type File, the system checks whetherthe file is located on the application server. If not, it cannot be selected.


Figure 126: BW Workspace Authorizations







The following user roles have been created for BW Workspaces:

• The BW Workspace Administrator creates BW Workspaces, defines theirproperties, make central data available in them and manages the BWWorkspaces.

• The business user can upload his/her own data for a BW workspace inWorkspace Designer and create CompositeProviders.

• The query user can execute queries on CompositeProviders belonging to aBW workspace.

To allow you to work with BW workspaces, SAP provides authorization templates,authorization proposal data and a role. The authorizations are assigned usingauthorization object S_RS_WSPAC (workspace name and activities).

Figure 127: BW Workspace Designer

BW Workspace Designer enables business users to easily create new modelsfor data analysis or enhance existing models. Various BW InfoProviders areavailable in the workspace. You can also upload your own providers. In aCompositeProvider, you can connect your own data to BW data by using union orjoin. This means you can react quickly to new or modified requirements.

Queries are usually based on MultiProviders. If new fields need to be added, theseMultiProviders have to be changed on the back end. BW Workspace Designerenables you to react quickly to new analysis requirements: This means you canadd fields to a query without changing the objects on the back end. The BWsystem administrator is still responsible for managing and checking the data fromthe BW system and for data storage (InfoProviders).

You might be planning a sales campaign for example and want to combine plandata with the actual sales data for 2010 and display ABC customer ranking datatoo. The plan/actual data has been stored in the BW in two InfoCubes that arecontained in a MultiProvider. You have saved the customers’ ABC ranking in








an Excel file. You upload the file with ABC data to your workspace. The twoInfoCubes are automatically connected by union in your workspace. You canthen link the data from your file by join.

Figure 128: BW Workspace Designer 1

Tab Page: CompositeProviders

Here you see a list of all CompositeProviders that have been created in theworkspace.

You can create, change and delete CompositeProviders here. By pressing DisplayData, you can view a CompositeProvider’s data. By pressing Inform User, you caninform a user by e-mail. If you select a CompositeProvider, its links and fields aredisplayed in the table at the bottom of the screen. You can then view a graphicaldisplay of the CompositeProvider and an overview of the associated queries. Hereyou can create, change and delete queries, as well as copy key figures.

You see the status of the CompositeProviders:

Draft: The CompositeProvider has been saved as a Draft but not activated yet.

Active: The CompositeProvider has been saved and activated.

Inactive: The CompositeProvider is given status Inactive if one of the localproviders it contains has been deleted.

Inactive (obsolete): The CompositeProvider used to have status Active and hasbeen changed and saved using Save Draft, but has not been activated yet.







If CompositeProviders have status Draft, queries can only be saved as drafts too.

Hint: You can copy calculated and restricted key figures, which havebeen defined for the individual InfoProviders of a CompositeProvider, asthe global key figures for a CompositeProvider.

Tab Page: Central Providers

Here you see a list of all the providers that have been assigned by the workspaceadministrator. These are providers that have been created centrally in the BWsystem and BWA indexed. Data content can be displayed and where-used lists runconcerning usage in CompositeProviders.

Tab Page: Local Providers

The uploaded providers are dislayed here together with information such as filesize.

You can create new local providers, delete existing ones, view data and createa where-used list.

Choose Reload Provider to load modified files from the original location or from adifferent one, and save them under the same name. This is only possible if thestructure of the file has not changed considerably. You can add new columns to theright, but cannot remove columns or change column headers. Use:

Reload (with Changes) if you have added new columns to the right in the file.

Load Directly if you have only modified the data and not the column structure.

Tab: Settings

In the Settings tab, you see general information, such as the name and prefix of theworkspace, the maximum memory space for your own workspace providers andthe memory space currently used by your own providers, contacts and the expirydate. You can also check whether the option is configured for saving your owndata in the database (only visible if you are using a BWA).

You can also check whether a MultiProvider has been defined. If an InfoProviderthat is contained in a defined MultiProvider is used in a workspace for modeling aCompositeProvider, the links in the MultiProvider are taken over as they are andcannot be changed manually.








Figure 129: BW Workspace Designer 2

Figure 130: BW Workspace Designer – Create Local Provider

Creating Local Providers

If you want to use data, which is not available on the BW system, in aCompositeProvider, you can upload this data manually to Workspace Designer. Todo this, create your own local providers that get data from files, BEx queries orDataSources.

Procedure

Select a type of source and choose Start.







Proceed as described below for the relevant source type:

Create Local Provider: File as Source

Create Local Provider: BEx Query as Source

Create Local Provider: DataSource as Source

Choose Upload Data. An analytic index is created and filled. You can now usethe data as a local provider in Workspace Designer.

Creating Local Providers: File as Source

Procedure

Select File

Select a file to upload to the workspace. The system can process text-based filescontaining comma-separated values (CSV files) and Microsoft Excel files.

You can specify the header that contains the field names.

Enter the first data row if it deviates from the default setting (in the default setting,the first data row is in row two).

For CSV files: Make settings for how separators, decimals, date and fieldseparators are displayed. The field separator sign can be used to set specialcharacters in the date field. If the field separator is contained in the date itself,it has to be set twice in the date field.

Note: If you CSV file is very large, and no field separator signs arerequired, you should remove the “” in order to improve load performance.

For the date, the format that the dates in the file are in has to be taken. Duringuploading, the date for storage in the analytic index is converted to the externalformat.

Note: With Excel files, the formatting generally taken from the file.Therefore, it is recommended that you format the columns appropriatelyin Excel files.

By choosing Display Data, you can see where the first data row begins, and howmany headers there are.

Enter a name and a description for the provider you want to create. The file namemust begin with the workspace prefix (if one has been set by the administrator).

Choose Continue.

Procedure

Selecting a Query







http://help.sap.com/saphelp_nw73/helpdata/en/70/868ad93e5e4f8a8f289664aeb5f307/content.htm

http://help.sap.com/saphelp_nw73/helpdata/en/fc/257a935f8f49769e9b5146ee26b81c/content.htm

http://help.sap.com/saphelp_nw73/helpdata/en/52/e726ee8f4241b6b7fb4eacab125311/content.htm


Select a BEx query. If a query contains variables, it can only be selected ifa previously created variant is selected. You can create variants directly inWorkspace Designer when creating the local provider, in the Query Monitor or inBEx 7.0.

More information: Query Monitor

For the BEx documentation: You can find more information in the SAP Libraryfor SAP NetWeaver, under http://help.sap.com.

Variants in BEx Web Applications: In the SAP Library, choose BusinessWarehouse → SAP Business Explorer BEx Web Analysis & Reporting: BEx WebApplications Using Variables in Web Applications Creating Query Variants.

Variables in BEx Analyzer: In the SAP Library, choose Business Warehouse →SAP Business Explorer Analysis & Reporting: BEx Analyzer Analysis ModeAnalysis → Functions Using Variables in BEx Analyzer Saving Query Variants.

Procedure

Select DataSource

Select a DataSource. You can choose from the following:

File DataSources

DB Connect DataSources

and UD Connect DataSources

SAP DataSources and export DataSources for which direct access has been set asPermitted on the Extraction tab page during definition.

Change Columns

The data types are determined automatically from the DataSource. The systemcan also tell whether it is a characterstic or a key figure.

You can change a key figure into a characteristic if it is a time stamp for example,and you want to use the time stamp as a character string.

You can set a filter to restrict the data volume during the upload.

Hint: We recommend setting ths filter, as the upload takes place in thedialog and therefore cannot be packaged. This helps to limit the time ittakes to upload the data. For larger amounts of data you should thereforecreate an InfoProvider in the BW system.

Select the fields that you need.

You can overwrite the field names.






http://help.sap.com/saphelp_nw73/helpdata/en/a0/2a183d30805c59e10000000a114084/frameset.htm

http://help.sap.com/


Figure 131: BW Workspace Designer – File as a Source (1)








Procedure

1. Select a file to upload to the workspace. The system can process text-basedfiles containing comma-separated values (CSV files) and Microsoft Excelfiles.

2. You can specify the header that contains the field names.3. Enter the first data row if it deviates from the default setting (in the default

setting, the first data row is in row two).4. For CSV files: Make settings for how separators, decimals, date and field

separators are displayed. The field separator sign can be used to set specialcharacters in the date field. If the field separator is contained in the dateitself, it has to be set twice in the date field.

Hint: If you CSV file is very large, and no field separator signsare required, you should remove the ‘ ” ’ in order to improve loadperformance. For the date, the format that the dates in the file are inhas to be taken. During uploading, the date for storage in the analyticindex is converted to the external format.

Hint: With Excel files, the formatting generally taken from thefile. Therefore, it is recommended that you format the columnsappropriately in Excel files.

5. By choosing Display Data, you can see where the first data row begins, andhow many headers there are.

6. Enter a name and a description for the provider you want to create. Thefile name must begin with the workspace prefix (if one has been set by theadministrator).

7. Choose Continue.







Figure 132: BW Workspace Designer – File as a Source (2)

Edit Columns

The system has analyzed the data.

For Excel files, the system has analyzed the formatting of the first data row anddetermined the data types from this. If a key figure has been formatted withoutdecimal places in the Excel file, the system proposes INTEGER as the data type.

For CSV files, see The Data Analysis for CSV Files

Deselect the fields that will not be needed later on. If you have specified a header,the field names are taken from this row.

If you have not specified a header, the field names are generated by the system.You can overwrite these field names.

The system has generated proposals for the field types of the individual columns.It proposes type Characteristic with the following data types: Character string,date or time.

You have to flag key figures yourself. The system then identifies the data typesInteger, Decimal or Floating Point Number. The data type ’decimal’ always hasthree decimal places. The data type ’floating point number’ is suggested for localdata with several decimal places. You can either accept this suggestion or switchto ’decimal’ (note that selecting ’decimal’ means that values are truncated afterthe third decimal place).

You can also select Character String with Leading Zeros or InfoObject as the type.If you assign an InfoObject, the internal format of the key figure is used.

Data Analysis for CSV Files

Before a CSV file is uploaded, the following parts of the file are analyzed:

The first 500 data rows (starting from the first data row)








500 rows in the middle of the file (for example, rows 750 - 1250 in a filewith 2000 rows)The last 500 rows

When uploading the file, the system might find a data type that does not match theanalyzed rows (if the analyzed files only contain numbers, and one of the rowsnot analyzed contains a character string for example). The upload is aborted, anda message is displayed with a recommended course of action: You either makechanges to the file (if it contains errors) and upload it again or you can changethe data type of the column.

Column-Based File Analysis

The system checks every cell of each column in the file using the followingpriority:

STRING/DATS/TIMS is always proposed. If a column is a key figure, you haveto select this. The system then determines whether it is a decimal, integer etc.

The date and date format of the cells are then checked. If the data in the contentmatches the data format selected in the application for uploading CSV files (orif the internal ABAP date format YYYYMMDD was selected with the formatoption YYYY.MM.DD), the cell content is identified as a date, and the data typeDATS is selected.

Finally, the system checks whether the cell contains a time characteristic. If this isthe case, the data type TIMS is selected.

In all other cases, the data type STRING is selected.

The ’leading zeros’ flag can be set for characteristics with the data type STRING.In this case, an alpha conversion is performed (CHAR field).

Figure 133: BW Workspace Designer – BW DataSource as a Source (1)








• File DataSources• DB Connect DataSources• UD Connect DataSources• SAP DataSources and export DataSources for which direct access has been

set as Permitted on the Extraction tab page during definition.


Creating Local Providers: DataSource as Source

Procedure

Select DataSource


File DataSourcesDB Connect DataSourcesUD Connect DataSources

SAP DataSources and export DataSources for which direct access has been set asPermitted on the Extraction tab page during definition.

Change Columns

The data types are determined automatically from the DataSource. The systemcan also tell whether it is a characterstic or a key figure.

You can change a key figure into a characteristic if it is a time stamp for example,and you want to use the time stamp as a character string.








You can set a filter to restrict the data volume during the upload.

Hint: We recommend setting ths filter, as the upload takes place in thedialog and therefore cannot be packaged. This helps to limit the time ittakes to upload the data. For larger amounts of data you should thereforecreate an InfoProvider in the BW system.

Select the fields that you need.

You can overwrite the field names.









Figure 137: BW Workspace Designer – Composite Provider

Procedure

1. If you want to use a specific query as the data basis, you can specify it here.The system finds the corresponding InfoProvider(s). Choose Start. Thewizard guides you through each step of the application.

2. Enter a name and description for your CompositeProvider. The filename must begin with the workspace prefix (if one has been set by theadministrator).

3. Select the required providers. You can select the central data assigned tothe workspace and your own data. If the list contains a large number ofproviders, you can find specific providers by choosing (Set Filter) or usingyour browser’s search function.

4. Press Continue. The system automatically takes the links from theMultiProvider if you use InfoCubes from the MultiProviders defined inthe workspace in your CompositeProvider. Choose Generate Proposal foreach individual provider to link the remaining fields. More information:Generating a Link Proposal

5. You can use the graphical view or the table view (lower screen area) to checkthe field connections. In the graphical view, the providers that are linkedwith each other as unions are displayed to the left of the CompositeProvider.The selected columns have been added to the CompositeProvider. Providersthat are linked using join are displayed on the right. In the tabular view, theCompositeProvider and its fields are displayed to the left. The connectedproviders are shown next to these. If you place the mouse pointer on theheader of the provider columns, the system displays additional information(for example, the number of linked fields, the number of display fields andhow many fields in the model have not been used). If you select DisplayAll Fields, the unused fields will also be listed at the end of the table. Forinformation about the graphical view, see: Graphical View.







http://help.sap.com/saphelp_nw73/helpdata/en/45/66ddad5b924d24863b74aed52bf08f/content.htm

http://help.sap.com/saphelp_nw73/helpdata/en/2d/b2353a6fce46afb658e3cce6606e50/content.htm


If the table is too large, and the headings are no longer legible, you canmodify the display: Open the context menu in the table preview and chooseUser Settings More. You can hide columns and restrict the number of rows(the rest is displayed using a scrollbar).

6. You can choose from the following link types: Union, Inner Join and LeftOuter Join. Key figures cannot be linked with connection type Join. Theconnection of InfoCubes participating in the MultiProvider defined in theworkspace is always Union, and the corresponding field link cannot bechanged. More information: Union / Inner Join / Left Outer Join

7. You can also create links manually. Choose Link Details. First, you canget the system to run the analysis for each field. To do this, choose DetailsComplete Proposal. The system now recommends which fields to link.For fields that are not linked, not linked is displayed in the Field ofCompositeProvider column. In this column, you can select a suitableCompositeProvider field from the drop-down list box. If you have selecteda field, the link is displayed immediately in the graphical view below. Theprovider to be joined is displayed on the left, and the CompositeProvideron the right.If you do not want link a field but still want to add it to the CompositeProvider,choose Standalone Field.Once you have made all required links, press Apply.

8. Choose Display Data to see a data preview. This enables you to checkwhether the links return the expected result. If the data preview does notreturn the expected result, you can analyze the join connections by choosingAnalysis. More information: Extended Checks.

9. Under Link Details, you can create a constant for connections of type Union.To do this, select a field and choose Link to Constant... Create.Under Link Details, you can also create simple calculations forcharacteristics. You can only use this function for local providers and withconnection type Join, and not for InfoProviders from the BW system. To dothis, select a characteristic of your provider and choose Create CalculatedCharacteristic. In the dialog, you can enter a name for the calculatedcharacteristic. You can choose from the following calculations:

Cut left (LEFTSTR)Cut right (RIGHTSTR)Cut middle (MIDSTR)Fill left (LPAD)Fill right (RPAD)







http://help.sap.com/saphelp_nw73/helpdata/en/77/23649b7a5b4ef3b86076fbc5b8d8d9/content.htm


ConcatenateNote: If you choose concatenate, you can also define a constant.To do this, just enter one character string and leave the second oneempty.

Note: During the calculation, note the differences between theinternal and external display. More information: External andInternal Display of Characteristic Values.

Once you have selected a calculation, the parameters for the calculation aredisplayed together with an example. Enter the parameters and press OK.Select the calculated characteristic to use. This will be added to the list ofCompositeProvider fields. Choose Return to CompositeProvider Modeling.

10. For Join connections: You can get the system to check whether key figuremultiplication might occur. To do this, select the provider linked by Join andchoose Analysis Check Key Figure Multiplication (for Join).

11. Further information about key figure multiplication: Union / Inner Join /Left Outer Join.

12. Press Continue. The system displays an overview of all CompositeProviderfields that will also be available in the query later on. You can now changethe field names.

13. For local providers, you can specify whether a unit or a currency should beassigned for key figures. These must be contained in the local provider.For key figures with a currency key such as 0AMOUNT, the assignment isautomatic. Press Continue.

14. You can now generate a standard query for your CompositeProvider, or usean existing query as a reference query. Select the query type.Standard: All fields in the CompositeProvider are added to the query as freecharacteristics or key figures. This query cannot be changed in BEx QueryDesigner. It changes automatically when the CompositeProvider is changed.If calculated or restricted key figures have already been defined on one ofthe InfoProviders that belongs to the CompositeProvider, you can select thisInfoProvider when defining the standard query.Reference: Select a BEx query that you want to reference. A referencedquery can be any query based on the assigned MultiProvider or one ofthe InfoProviders being used. As soon as an InfoProvider is used in theCompositeProvider that is contained in the assigned MultiProvider, it is onlypossible to select queries that are based on the MultiProvider.Changes to the referenced query have an immediate effect on the transientquery. However, the referenced query can only contain fields that are alsocontained in the CompositeProvider. If it contains other characteristics in thefree characteristics, these are removed in the reference query.

Note: This allows you to use calculated key figures from thereferenced query for example.







http://help.sap.com/saphelp_nw73/helpdata/en/e1/492cb2aacc475b9260fac373426678/content.htm

http://help.sap.com/saphelp_nw73/helpdata/en/e1/492cb2aacc475b9260fac373426678/content.htm




Press Continue.

15. The system displays an overview of all objects that you have defined.16. Choose Save and Generate. The CompositeProvider and associated queries

are now generated.

Figure 138: BW Workspace Designer – Create Composite Provider 1

In a CompositeProvider, you can combine all the data that you want to view inyour query. You can use all central BW InfoProvider that have a BWA index(InfoCubes, InfoObjects as InfoProviders, analytic indexes, VirtualProviders,queries as InfoProviders etc.) and are assigned to the workspace as data providers,as well as your own data (in the form of uploaded Microsoft Excel/CSV files,uploaded query results or uploaded data from DataSources).








Union / Inner Join / Left Outer Join

A union combines data from multiple providers and builds the union sets for therelevant data. All the values are combined.

A join combines two tables by using specific criteria. You can choose betweeninner join and left outer join.

The inner join combines data from both tables if all the specified criteria are met.If one or more criteria are not met, no data records are created in the result set.

The left outer join takes all the values from the left table and combines them withthe values from the right table that meet the criteria. All the values from the lefttable are included in the result table, even if they do not meet the criteria. If theleft table returns a table row and the right table returns more than one watchingrow, then the values of the left table are repeated for every row in the right table.

Inner Join / Left Outer Join Comparison

If a product has not been assigned to any product groups for example, this productwill not be displayed with an inner join, but will with a left outer join instead.









Graphical View

The graphical view shows you the CompositeProvider and the components is itmade up of, with all unions, joins and their fields. If you are using a MultiProvider,the system displays the entire MultiProvider, not the individual InfoProviders itcontains.

There are two views to choose from:

You can view the entire CompositeProvider or toggle the display to Join Only.With this option, only the joins and their join conditions are displayed. If severaljoins are built up one behind the other, this is displayed accordingly in thisview. You can also see how many providers each field is still linked with (+3for example).

Properties of the Display

You can acquire the following information from the font and the colour of the text:

• Black text: Normal provider fields• Italic text: Calculated characteristic and constant• Blue text: Join field• Red text: A field that is contained in the CompositeProvider but is no longer

available in the provider• Grey text: The field exists but is not used in the CompositeProvider

You can hide unused fields by choosing Hide Unused Fields in the context menu.You can use the context menu in the background to set this setting globally. Thenumber of hidden fields is displayed in brackets after the number of displayedfields.







The descriptions of the fields are displayed in the language defined in the languagesetting. If there is no description available in the logon language, the technicalname is displayed instead. Otherwise, the technical name appears in the field’stooltip if the user has performed a mouseclick in the grey background field.

To provide a better overview, you can expand and collapse providers. This canbe set for all providers in the context menu in the background and for individualproviders in the context menu on the provider’s header row. You can also use thearrows to collapse characteristics and key figures separately. Connections betweencollapsed providers are shown using dotted grey lines.

Settings

Settings allows you to hide entire providers, to modify the horizontal distancebetween the nodes and to deactive automatic highlighting. The AutomaticHighlighting setting is activated in the standard setting, but only works in theDisplay: CompositeProvider and highlights all links if the user clicks with the leftmouse button on a field in the provider.

You can also change the zoom factor, print the preview and use the navigator toswich to the required location if you have a very large view.

The settings that you make here are non-CompositeProvider specific. The systempersonalizes them and stores them under your user.











You can now generate a standard query for your CompositeProvider, or use anexisting query as a reference query. Select the query type.

Standard: All fields in the CompositeProvider are added to the query as freecharacteristics or key figures. This query cannot be changed in BEx QueryDesigner. It changes automatically when the CompositeProvider is changed.

If calculated or restricted key figures have already been defined on one ofthe InfoProviders that belongs to the CompositeProvider, you can select thisInfoProvider when defining the standard query.







Reference: Select a BEx query that you want to reference. A referenced querycan be any query based on the assigned MultiProvider or one of the InfoProvidersbeing used. As soon as an InfoProvider is used in the CompositeProvider that iscontained in the assigned MultiProvider, it is only possible to select queries thatare based on the MultiProvider.

Changes to the referenced query have an immediate effect on the transient query.However, the referenced query can only contain fields that are also contained in theCompositeProvider. If it contains other characteristics in the free characteristics,these are removed in the reference query.

Note: This allows you to use calculated key figures from the referencedquery for example.


Activating Data Backups for Local Providers

You can activate data backups for local providers for each BW workspace.Backups of the uploaded data (of the local providers that is) are then created inthe database. These backup copies are then available in case data needs to berecovered at some stage. They are also needed if data is migrated from the theBW system to an SAP HANA database.

You can only use this function if you are using a BWA. If you are using a SAPHANA database, a DB backup is performed instead (primary persistence).

You are in the workspace editing screen. Choose the Settings tab.

Under Settings for Local Providers, choose Back Up Data.

Hint: This setting cannot be changed any more once there are localproviders in the workspace.








You can use program RSL_WSP_BACKUP_DELETE to deactivate the databackup for selected BW workspaces. The backup copies of all associated localproviders (the uploaded data) are deleted. After the program has been run, the databackup function is inactive for the selected workspaces, meanting that no databackups are performed for subsequently uploaded data.







Lesson Summary

You should now be able to:• Leverage SAP BW Workspace







BW362 Unit Summary

Unit SummaryYou should now be able to:• Leverage SAP BW Workspace






Unit Summary BW362







Unit 6161 Layered Scalable Architecture without

SAP HANA

Unit OverviewContent of this unit is Layered Scalable Architecture without SAP HANA


• [Enter a lesson objective.]• [Enter a lesson objective.]

Unit ContentsLesson: Layered Scalable Architecture without SAP HANA .... . . . . . . . . . .166






Unit 6: Layered Scalable Architecture without SAP HANA BW362

Lesson:162

Layered Scalable Architecture without SAP HANALesson Duration: 120 Minutes

Lesson Overview[Enter a brief overview of the lesson.]


• [Enter a lesson objective.]• [Enter a lesson objective.]


Business Example[Enter a business example that helps the learner understand the practical businessuse of this lesson.]

Figure 145: Key Benefits of Enterprise Data Warehousing (1)







BW362 Lesson: Layered Scalable Architecture without SAP HANA

Figure 146: Key Benefits of Enterprise Data Warehousing (2)

Figure 147: Corporate Information Factory (Bill Inmon)







Figure 148: LSA Goals – Standardization, Transparency, Efficiency

Figure 149: BI Projects Built on Customer LSA Standards








Figure 150: Layered Scalable Architecture: Reference Layers

Figure 151: Data Acqusistion Layer

Figure 152: Harmonization Layer







Figure 153: Propagator

Figure 154: Corporate Memory

Figure 155: Business Transformation Layer








Figure 156: Architected Data Mart

Figure 157: Virtualization Layer







Figure 158: Operational Reporting within Classic Data Warehousing

Figure 159: Operational Data Store








Figure 160: LSA: Domain Concept

Figure 161: LSA Building Blocks: Extract Once – Deploy Many







Figure 162: LSA Domain Concept – Strategic BW Partitioning Accross theLayers – For All Flows

Figure 163: LSA Data Flow Templates Overview








Figure 164: LSA Data Flow Template 320

Figure 165: LSA Implementation For Transactional Data







EXAMPLE – Enterprise Procurement Model

Figure 166: EPM Model

Figure 167: EPM Model: ITelO – A Retail Company

Figure 168: EPM Model: Business Process








Figure 169: EPM Model: Business Objects

Figure 170: EPM Model: Data Generator (SEPM_DG)







Lesson Summary

You should now be able to:• [Enter a lesson objective.]• [Enter a lesson objective.]







BW362 Unit Summary

Unit SummaryYou should now be able to:• [Enter a lesson objective.]• [Enter a lesson objective.]






Unit Summary BW362







Unit 7177 Layered Scalable Architecture plus

plus (LSA++) with SAP HANA

Unit OverviewContent of this unit is Layered Scalable Architecture plus plus (LSA++) withSAP HANA


• Describe the concepts of LSA++

Unit ContentsLesson: Layered Scalable Architecture plus plus (LSA++) with SAPHANA .... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .182






Unit 7: Layered Scalable Architecture plus plus (LSA++) with SAP HANA BW362

Lesson:178

Layered Scalable Architecture plus plus (LSA++) withSAP HANALesson Duration: 120 Minutes

Lesson OverviewSAP HANA specific extensions of the LSA, leading to LSA++ are discussed.


• Describe the concepts of LSA++


Business ExampleYour company has a BW system whose architecture follows the principles of LSA.Now, an upgrade to BW, powered by SAP HANA is made. The new possibilitiesoffered by the new technology shall be used by introducing an LSA++ architecture.

Figure 171: In-Memory Evolution SAP NetWeaver BW

One of the most important aspects of in-memory technology consists in theparadigm shift that states that data-intensive business logic shall be pushed downto be calculated by the database instead of the application server. In BW, as the BWaccelerator exists for some years already, this in-memory programming paradigm







BW362 Lesson: Layered Scalable Architecture plus plus (LSA++) with SAP HANA

has been followed for several years already. Starting with filter and aggregationfunctions in times of BWA 7.0, calculation functionality has been moved to becalculated on the in-memory machine more and more, until the full mass datamanipulations are done on the database server in times of BW on HANA.

Figure 172: Key message No. 1:

Even if no further changes are made to a well-designed layered scalablearchitecture, the migration of the database to HANA will show significantperformance gains:

1. The query performance will be significantly faster.2. There will be less volume on the database even if the data volume itself

remains the same, since indices are no longer necessary.

Migrate to HANA-Optimized ObjectsTo profit fully from the new possibilities that SAP HANA offers as a databasebelow a SAP NetWeaver BW system, several steps may be followed. These stepswill be discussed in detail in the upcoming slides.

Figure 173: From LSA to LSA++







As a first step, after the technical migration of the database to SAP HANA, the BWobjects should be migrated to SAP HANA-optimizes BW objects. This concernsInfoCubes, DataStore-Objects and Sematically Partitioned Objects (SPOs).

Figure 174: Performance Gains After Migration

Query Performance:

• Flat InfoCubes contain master data SIDs directly in the fact table. Nodimension tables exist that need to be joined during query runtime.Therefore, the read performance is enhanced.

• Reading from a DSO is faster, due to the columnar storage and parallelexecution of read processes.

• Calculations and aggregations are faster, since they are evaluated by thedatabase server instead of the application server.

Load Performance:

• Data Activation uses the Delta Merge mechanism of the SAP HANAdatabase, replacing the old algorithm. This results in up to 10-fold speed-up.

• During Data load into InfoCubes no DIM-IDs have to be created. Thissaves time.








Streamline EDW Core


Firstly, the layers of the LSA that make up the core of the EDW are called “EDWCore”. This includes all layers that hold the data in consolidated, harmonized way,i.e., data that conforms to the data quality that is defined as the BW standard asserves as the reliable trustable single point of truth throughout the corporation.

Streamlining the EDW core means to check to which degree it is necessary to keepthe layers persistent. In some cases, it may be possible to replace a persistent layerwith a virtual layer, thus saving data volume and gaining load performance.

Figure 176: LSA++: Streamlined EDW and Architected Data Marts







Figure 177: LSA++: Reliable, Consistent, Flexible EDW Core

Figure 178: LSA++: Streamlining EDW Core








Figure 179: Streamlined EDW – Virtualization of InfoCubes – Obsolete:InfoCubes as Accelerator on Business Transformation Layer DSOs

If the reason for the existence of an InfoCube is in that the InfoCube holdspre-aggregated data with the sole reason of speeding up query runtimes, then thisInfoCube (or SPO) can be dropped. This is the case when the transformationleading into the InfoCube contains 1:1 mappings only and the InfoCube is lessgranular than the DSO. All information necessary for the queries is contained inthe DSOs as well as in the InfoCubes. Thus, no information is lost upon deletionof the InfoCubes.

In practice, it should always be determined whether the query runtime whenreading from the underlying DSOs is really satisfactory before the InfoCube isdeleted. Transaction RSRT.







Figure 180: Streamlined EDW – EDW Propagation Layer as Query Target

Same reasoning as before.

In LSA++, other than in LSA, we allow reporting on the propagation layer.

Figure 181: Streamlined EDW – Virtualization of InfoCubes – EliminatingInfoCubes – Things to Keep in Mind

Enhance Virtualization LayerStreamlining the EDW core results in minor changes to the Enterprise DataWarehousing architecture. It does not yet utilize any of the new functionalities thatBW on HANA offers.









With enhancing the Virtualiziation Layer, the first additional options are utilized.

In LSA, the Virtualization Layer consists of MultiProviders. MultiProviders offeran enhanced query performace, due to query pruning. In rare cases, InfoSets maybe used. However, since InfoSets conduct a join of the data during query runtimeand this join is calculated by the application server, queries on InfoSets are veryslow. Thus, in classic LSA, unions can be made, whereas joins should be avoided.

With BW on HANA, CompositeProviders can be used to join data.CompositeProviders may contain PartProviders that are all persistent, i.e., thatstem from the underlying EDW core.

In this animation, the path from the classic LSA architecture with its consistentEDW Core towards a streamlined flexible consistent EDW Core is shown,followed by depicting the enhanced Virtualization Layer.

Figure 183: Streamlined EDW – Virtual Data Mart Layer







LSA:

• No reporting on Propagator• Result of transformations stored in additional persistent Layer, i.e.

Architected Data Mart• Virtualization Layer only on top of Architected Data Mart and only UNION

(MultiProvider)

LSA++:

• Reporting on Propagator is allowed• Consequenty, necessary transformation are moved from the Business

Transformation Layer into Query Design and are thus executed uponmquery execution.

• Virtualization layer on top of both Architected Data Marts and Propagatorand using UNION (MultiProvider) and JOIN (CompositeProvider)

Hint: Sometimes it is necessary to store the result of a transformationin an InfoCube for reasons other than performance reasons or technicalreasons. Often, the transformed data (i.e., after a currency conversion)shall be stored and archived to match a given Service Level Agreementregarding data quality and audit proofness. If it is essential that a reportcan be reproduced at any time, regardless of the key date of the query, thenthe storage requirement is given due to business reasons.

Figure 184: CompositeProviders – Virtualization or Persistent Join?








Figure 185: Virtual Data Mart Layer: CompositeProviders

Figure 186: Decision Criteria on Using Composite Provider – ArchitectedData Marts and BW Virtual Data Mart Layer

The more complex a transformation is and the higher the data volume is, the morelikely it will be to keep the Data Mart.

If the transformation logic is simple (and can easily be incorporated into a querydefinition) and the data volume is small (thus only a small volume needs to beevaluated at query runtime), the data mart may be dropped.







Introduce Additional (++) Layers


The Open Operational Data Store (LSA++) replaces the Data Acquisition Layer(LSA) and the Operational Data Store (LSA).

Data are available as in the source model (i.e., not in the BW model) and areof source-level quality.

The Open Operational Data Store serves two requirements:

1. Initial staging: from here, data can be loaded into the flexible consistentEDW Core and undergo quality checks and harmonizations

2. Operational Reporting

Open Operational Data Store

Figure 188: LSA++: Open ODS Layer

Any data coming from any source system is firstly organized into the OpenOperational Data Store.








If classical Staging technology is used, i.e., a DataSource with its PSA table thatis filled upon execution of an InfoPackage, the data delivery takes places undercontrol of BW or BW-managed. Of course, the data is stored in the database,i.e., on HANA. This part of the Open Operational Data Store is the successorto the Data Acquisition Layer.

It is also possible that data provisioning methodes such as SLT are used to pushdata directly into HANA (however, into a schema different from the BW schema).These data may also be made usably in the BW system. We then speak ofexternally managed data that is delivered directly to HANA. This part of theOpen Operational Data Store combines features of the Operational Data Store(LSA) with new features that come with BW on HANA.

Figure 189: LSA++ for BW on HANA – A Holistic Framework – LSA++Principal Layers & BI Value Areas

This animation shows how the Open Operational Data Store Layer replaces boththe Data Acquisition Layer and the Operational Data Store.

Unlike in LSA, LSA++ allows reporting on data that resides (either persistentor realtime-accessible) in the Open Operational Data Store. Thus, finally theVirtualisation Layer is extended so as to wrap not only the Data Mart Layer andPropagation Layer, but also the Open Operational Data Mart Layer.







Figure 190: LSA++ Open ODS Layer: Services

BW EDW Services

• BW managed data• Source for persistent EDW providers: previously Data Acquisition layer

in LSA• Data Acquisition Layer in LSA did not allow reporting• Open ODS Layer now allows reporting. Some VirtualProvider should be

modeled on top of the persistent provider holding the incoming data. Thismakes open ODS layer providers the persistent data bin for queries built ontop of the VirtualProvider.








→ Reporting on operational data is supported

• BW Operational Data Services

– Externally managed data if Virtual Provider, BW managed data if RDAwith realtime InfoPackgae

– Realtime Data Acquisition: previously Operational Data Store (ODS)layer in LSA

– Consumption of data possible as soon as data are loaded into BW,independent on load technology (i.e., staging versus RDA)

– Field-level data can be remodeled using BW modeling techniques (i.e.,DSO or HybridProvider)

• BW Integration Services

– Externally managed data– No comparable layer in LSA– Consumption of HANA data in BW: VirtualProvider, publishing

HANA model into analytical index– Transfer HANA data into BW: via DB Connect

Figure 191: LSA++ Open ODS Layer (I): Source for Persistent EDW Providers(1)

In the aspect of data staging into the flexible consistent EDW core, the OpenOperational Data Store serves the function of the Data Acquisition Layer. Dataare loaded with InfoPackages into the PSA tables of DataSources. Then, the dataare run through the EDW Transformation Layer (harmoniziation, data qualitychecks, consolidation, …) into the Propagation Layer. From the inbound OpenOperational Data Store, data are also updated to the Corporate Memory.







Figure 192: Real-time Data Replication to SAP BW using SAP LT ReplicationServer

Apart from using classical staging techniques that rely on a scheduled InfoPackage,realtime replication using LAP Landscape Transformation (SLT) can be now beused. A a target, a Web Service DataSource is used. The write module of the LTReplication Server is then calling the RFC-enabled function module that updatesthe data into the PSA. The data may then be uploded into a DataStore-Objectusing RDA techniques with a daemon.

SAP Notes

• Note 1709225 – Installation / Upgrade LT Replication Server – DMIS 2010SP7

• Note 1710532 – HANA LTR (2010 SP07 #2) General correctons 1








Figure 193: BEx Querying on BW Field-level Data – Operational DSO(planned for BW 7.40 / 2013)

In the future, it will be possible to replicate data using SLT into an OperationalDataStore-Object. The Operational DataStore-Object is a new type of DSO that isannounced to be introduced with SAP NetWeaver BW 7.40 in 2013. It remainson field level, thus no InfoObject modeling needs to undertaken to create anOperational DataStore-Object. Nevertheless, BEx Queries can be defined usingan Operational DataStore-Object as an InfoProvider.

Figure 194: LSA++ Open ODS Layer (I): Source for Persistent EDW Providers(2)







Overview of the different levels of modeling and role of the Open OperationalData Store Layer as incoming layer receiving data from the source systems andsupplying the flexible consistent EDW Core.

Figure 195: LSA++ Open ODS Layer (II): Supports Immediate Querying

In LSA:

RDA into DataStore-Object via RDA-enabled DataSource located in the DataAcquisition Layer. The DSO is located in the Operational Data Store (ODS) Layer.

When the daily reporting activity has ended, the open RDA request will be closedand can now be uploaded via scheduled process chains into the EDW layers.

In LSA++:

The Open Operational Data Store Layer hosts all activities necessary to supportoperational reporting on field level in realtime. Via scheduled process chains,the data will be uploaded into subsequent EDW layers. Only then will theimplemented quality checks be executed.

Considering the objects involved (i.e., DataSource, DSO as target for RDA,propagator DSO, transformation into propagator DSO in which harmonization andquality checks take place) there is no change in this particular scenario. However,the conceptual view, i.e., the birds perspective has changed. The change of theconceptual framework allows to open new perspective on additional integrationscenarios. In particular, BW Integration Scenarios can now be incorporated intothe conceptual framework.








Figure 196: LSA++ Open ODS Layer (III): Integration Services (1)

Integration Services within the Open Operational Data Store allow to consumeSAP HANA models within BW.

The BW system runs on the ABAP stack of the application server.


Below the application server is the database. In case of BW, powered by SAPHANA this is a SAP HANA database. More specifically, it is specific databaseschema within HANA, i.e.m the BW schema.








It is possible to run applications different from SAP NetWeaver BW on thesame SAP HANA system. This, however, requires a second schema within theHANA system. Using data from the second HANA schema, SAP HANA modelscan be built using SAP HANA technology for rapid data marts (analytic views,calculation views). These SAP HANA models are completely independent fromthe BW models and may, for example, be directly consumed with BI 4.0 tools.









However, it is possible to integrate both worlds by consuming the SAP HANAmodels in BW. To do so, different techniques are available. They include thepublishing of SAP HANA models into BW as analytical indices that can be usedas TransientProviders from BW queries or VirtualProviders based on a SAPHANA model.

Figure 200: Use Case Integration Service: Multiple Applications On a SingleSAP HANA System

In special cases, it is possible to run several SAP applications on a singe SAPHANA system (see SAP note 1661202). As an example, it is possible to run aBW system and a CO-PA Accelerator on a single SAP HANA system. Within theSAP HANA system, the two applications will store their data in strictly separatedatabase schemas.

Data is loaded into the SAP BW schema via the extraction, transformation, andloading (ETL) process, using the staging technology upon which the LSA++Enterprise Data Warehousing architecture is built. Data is consumed via BExqueries defined on SAP BW InfoProviders. BI 4.0 reporting tools may be used todisplay the data to the end user.

Data is loaded into the CO-PA Accelerator schema via realtime data replicationtechniques, in particular SLT. Only the ERP tables relevant for the CO-PA scenariowill be replicated. Within the SAP HANA system, SAP HANA content is builton top of the replicated tables. In the CO-PA Accelerator scenario, these HANAcontent models are consumed using BI 4.0 reporting tools directly.

The two applications are completely independent of each other. However, it maybe useful to be able to consume the CO-PA HANA models not only using the BI4.0 reporting suite directly, but to consume the CO-PA HANA models using theBW technology, incorporating it into the Enterprise Data Warehouse (LSA++).This consolidates the reporting landscape, since reporting is centralized in the BW







system rather than split across applications. In addition, the SAP HANA CO-PAcontent may be combined with consolidated EDW data (Agile Data Marts andBW Workspaces, see next Sections).

Figure 201: Available HANA Finance Accelerators

Use case Integration Service of the Open Operational Data Store: Integrating SAPHANA Accelerator Content into BW.

Apart from the CO-PA Accelerator, there are a number of additional Acceleratorsavailable, whose number and range is expanding. In general, in the acceleratorarchitecture, SAP HANA serves as secondary database below an ERP applicationserver. The relevant ERP tables are replicated (using SLT) from the primarydatabase into the secondary database. When data are accessed, they are read fromHANA instead of from the primary database, thus speeding up the read process.Thus, the known user interfaces (including operational reporting techniques) fromthe ERP system are presented to the end user.

In addition, however, SAP HANA content is developed to support operationalreporting on the designated ERP data. This HANA content is delivered along withthe accelerators and consists of Analytic Views and Calculation Views. It may beconsumed directly using BI 4.0 tools.

Since it is allowed to run SAP NetWeaver BW, powered by SAP HANA and anERP accelerator on the same SAP HANA system, it may be useful to incorporatethe Accelerator HANA content into the BW system in order to ensure that allreporting necessities are bundled in one single system, i.e., the BW system. Forthis purpose, it will be useful to publish the Accelerator SAP HANA models intoBW and consume them via a BEx query on the analytic index (the end user needsto log on the BW application server) instead of using the BI 4.0 tool suite directly(the end user needs to log on to the HANA database).








Figure 202: Use Case Integration Service: Analytics Framework

Use case Integration Service of the Open Operational Data Store: IntegratingAnalytics Framework into BW.

As a new way of supporting analytic solutions for operational reporting purposes,SAP delivers the SAP HANA Analytics Framework for the SAP Business Suite.It is based on replicating ERP tables from the primary ERP database into the SAPHANA database. On HANA, pre-delivered HANA content built on the physicaltables provides re-usable views as well as public views. The delivered content isextensible by customers. The Consumption Views can then directly be consumedby different clients, i.e., the BI 4.0 tools.

It may also be published into BW to integrate all reporting activities into a singlereporting system. The BW system thus serves operational reporting needs (OpenOperational Data Store) as well as strategic reporting needs (Consistent flexibleEDW Core).







Figure 203: LSA++ Open ODS Layer (III): Consume HANA Model in BW

There are different levels of integration between SAP HANA models and BWmodels.

Unique to BW is the handling of master data using InfoObjects. The level ofintegration depends on the question whether the master data that is used in theHANA model is modeled within the BW Warehousing Architecture.

A tight integration is possible when InfoObjects are available for all fields. In thiscase, it needs to be decided whether the data shall be permanently stored in BWor not. I storage is required, a standard InfoProvider can be modeled and loaded.A HANA schema other than the BW schema can be accessed via DB Connect.If no permanent data storage is required, a VirtualProvider based on a HANAmodel can be used.

If InfoObjects are not available or not available for all fields of the HANAmodel, then the HANA model can be published into an Analytic Index and beconsumed as a TransientProvider. For those fields, for which InfoObjects areavailable, the InfoObjects may be assigned to the fields, thus allowing to usethe standard BW features (texts, attributes, hierarchies) in the reports built onthe TransientProviders.








Figure 204: Different Levels of Model-Integration of Field-level Data

Figure 205: Different Levels of Integration of Field-Level Data – VirtualProvider on HANA Model







Figure 206: Different Levels of Integration of Field-Level Data – TransientProvider & Transient InfoObjects on HANA Model

Figure 207: LSA++ Open ODS Layer (III): Integration Services

It is not only possible to publish a HANA Analytic View into BW, but also viceversa. A BW InfoCube can be published into SAP HANA. In HANA, it becomesan Analytic View that can be consumed like any other Analytic or CalculationView.








Figure 208: Import SAP BW InfoCube into SAP HANA (1)

Figure 209: Import SAP BW InfoCube into SAP HANA (2)







Agile Data Mart Layer and BW Workspace Layer


The Agile Data Mart Layer and the BW Workspace Layer are additional layersthat host objects that put Warehouse data together with operational regional (AgileData Mart) or departmental to even individual (BW Workspace) data.

On InfoProvider level this is achieved by splitting the Virtualization Layer into aWrapping Layer and a Compositition Layer. The Wrapping Layer consist of theMultiProviders sitting on top of the EDW data. The Composition Layer consistsof CompositeProviders that merge data from the Open Operational Data Storewith the wrapped EDW data (Agile Data Mart) or Analytic Indices in the formof LocalProviders from uploaded BW Workspace data with wrapped EDW data(BW Workspace Layer).

Figure 211: LSA++: Integrating Open ODS with EDW Core








Figure 212: LSA++: Virtual Data Marts on Open ODS and/or EDW

Agile Data Mart Layer: Allows continuous grade of operational to quality-ensuredEDW data.

Figure 213: LSA++ Virtual Data Mart Layer Structuring

Splitting up the Virtualization Layer into Wrapping Layer and Composition Layerto support any reporting requirement on the continuum between operationalreporting (Open Operational Data Store) to long-time strategic reporting (flexibleconsistent EDW Core).







Figure 214: Virtual Data Mart Layer: Composition Layer

The Composition Layer consists of CompositeProviders, designed with Backendmeans (transaction RSLIMOBW). This refers to the Agile Data Mart Layer.

Figure 215: Virtual Data Mart Criteria for Structuring – Naming Proposal








Figure 216: LSA++: Agile Data Mart Layer

This animation shows how the LSA++ architecture is enhanced with the AgileData Mart Layer.

Figure 217: LSA++: BW Workspace Layer

In addition to the Agile Data Mart Layer, the LSA++ is enhanced with the BWWorkspace Layer. The BW Workspace Layer is in principle similar to the AgileData Mart Layer. However, here, the data that is “agile” will uploaded intoAnalytic Indices in the form of LocalProviders by the endusers. The tool to bothupload personal or departmental data and to merge the personal data with EDWdata using a CompositeProvider is the NW BusinessClient driven BWWorkspaceDesigner.







Figure 218: Virtual Data Mart Layer: Composition Layer

Figure 219: Corporate Master Data and Local Attributes

Figure 220: LSA++: Agile Extensions (1)

In which layer should a new InfoProvider reside? To answer that question, theownership, quality level, and source of the data need to be evaluated.








Figure 221: LSA++: Agile Extensions (2)

This matrix allows a first guess as to where an InfoProvider should be allocated.

Resulting LSA++








Figure 223: LSA++ Holistic Framework – Virtual Data Marts: VirtualWrapping & Combining Data

Figure 224: LSA++ Holistic Framework for BW on HANA

And now, as the happy end, a one-slide overview of all layers of the LSA++ thathave been discussed in this Section.








EXAMPLE – Enterprise Procurement Model

Figure 225: EPM Model: Business Process

Figure 226: EPM Model: Reporting







Lesson Summary

You should now be able to:• Describe the concepts of LSA++







BW362 Unit Summary

Unit SummaryYou should now be able to:• Describe the concepts of LSA++






Unit Summary BW362







Unit 8215 Exercises

Unit OverviewContent are the exercises of unit 8


• SAP BW on HANA

Unit ContentsLesson: Exercises ... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .221

Procedure: Exercise : 1 - Using SAP HANA Studio .. . . . . . . . . . . . . . . . . .222Procedure: Exercise : 2 - SAP BW Tables in SAP HANA.... . . . . . . . . .234Procedure: Exercise : 3 - HANA-Optimized DataStore-Object.. . . . . .237Procedure: Exercise : 4 - HANA-Optimized InfoCubes ... . . . . . . . . . . . .249Procedure: Exercise : 5 - HANA-Optimized SPO.... . . . . . . . . . . . . . . . . . .252Procedure: Exercise : 6 - HANA VirtualProvider .. . . . . . . . . . . . . . . . . . . . . .258Procedure: Exercise : 7 - TransientProvider.. . . . . . . . . . . . . . . . . . . . . . . . . . .263Procedure: Exercise : 8 - CompositeProvider .. . . . . . . . . . . . . . . . . . . . . . . . .267Procedure: Exercise : 9 - DB Connect .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .271Procedure: Exercise : 10 - Create Workspace ... . . . . . . . . . . . . . . . . . . . . . .274Procedure: Exercise : 11 - Workspace Designer to Create LocalProviders From A File .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .277Procedure: Exercise : 12 - Workspace Designer to Create A LocalProvider From A BW DataSource ... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .290Procedure: Exercise : 13 - Workspace Designer to Create ACompositeProvider .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .293Procedure: Exercise : 14 - Consume CompositeProvider Using SBOAnalysis for MS Excel .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .299






Unit 8: Exercises BW362

Procedure: Exercise : 15 - Case Study – EPM Model .. . . . . . . . . . . . . . .303Procedure: Exercise : 16 - Design LSA for Case Study ... . . . . . . . . . . .305Procedure: Exercise : 17 - LSA → LSA, powered by SAP HANA ..306Procedure: Exercise : 18 - LSA, powered by SAP HANA → LSA++(Optional) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .308Procedure: Exercise : 19 - Optional: LSA++, Evaluation of AdditionalReporting Scenarios.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .310







BW362 Lesson: Exercises

Lesson:217

ExercisesLesson Duration: Minutes

Lesson OverviewExercises


• SAP BW on HANA

Business ExampleExercises







218Exercise : 1 - Using SAP HANA StudioUse

Note: Please fill out the details given by the instructor and use these forall exercises:

Remote Desktop Alias

Remote DesktopUsername

train-XX

Remote DesktopPassword

initial

SAP HANA DatabaseHost

wdflbmtXXXX.wdf.sap.corp

SAP HANA DatabaseInstance

01

SAP HANA DatabaseUsername

studentXX

SAP HANA DatabasePassword

Training1 (case sensitive)

SAP BW Server wdflbmtXXXX.wdf.sap.corp

SAP System ID CIA

SAP BW Instance 02

SAP BW Mandant 003

SAP BW User USERXX

SAP BW Password INITIAL

SAP Business ClientName

BW on HANA

SAP Business ClientSystem

http://wd-flbmtXXXX.wdf.sap.corp:XXXXX/NWBC

SAP Business Client -Client

003

SAP Business Client -Language

EN

This section includes an exercise on look and feel of SAP HANA Studio.In this exercise you will log on to the WTS server, and get familiar withnavigating in SAP HANA Studio. You will complete the exercise bycreating your own Information Package.

Continued on next page








Procedure1. If you logon via VDI landscape please follow the instruction given by your

instructor otherwise logon to the WTS landscape:

• Go to Start-Menu• Start menu: Choose Common-Training

2. Remote Desktop into Server

• Create a remote desktop connection to another desktop (connectioninformation will be given by the instructor)

• Start the Remote Desktop Connection as shown in the screenshot onthe right side.

• Use the path: Start Menu → All Programs → Accessories.

Figure 227: Remote Desktop Connection

3. In the next screen you have to choose one of the available remote desktopservers.

Note: Type the name of the Server (specified by your instructor).

• Click → Connect.








Figure 228: Select Remote Desktop Server

4. In the Remote Desktop Connection dialog box enter user name and passwordgiven by the instructor.

Figure 229: Logon

5. Now you are on the right desktop and can start the SAP HANA Studio bygoing to Start → Studio.









Figure 230: SAP HANA Studio

6. Open Administration Console

Hint: Hit “x” to close the overview screen.

Figure 231: HANA Administrator Console

7. Register a new System.

Right Click within the Navigator view and choose→ Add System....

• Enter the Hostname, Instance Number and Description as given bythe instructor.








Hostname wdflbmt7211.wdf.sap.corp

Instance Number 01

Description SAP BW on HANA

Locale English (United States)

• Click → Next.

Figure 232: Register a New System

Figure 233: Click Next

8. Enter your credentials as given by your instructor.









Figure 234: Connection Properties

9. Change your initial password

• Minimum 8 characters• Must contain capital and small letters• Must contain numbers• Example: Abcd1234

Hint: If prompted for a security fallback for your password, clickNo.

Note: If your HANA system is not properly connected to the SAPHANA Studio (status is red), choose Refresh from the context menu.

If necessary, close and reopen the SAP HANA Studio.








Figure 235: Change Initial Password

10. The first customization you should do is now to adjust the default setting ofthe default client in the studio preferences.

• Therefore go in the top menu and choose Window → Preferences...

Figure 236: Choose Window - Preferences









11. Next, expand the Modeler node in the tree and click on Default ModelParameters.

• Now ensure that the client is 800.• Maybe you must change it from dynamic to 800. Press the button Apply.

Figure 237: Default Model Parameters

12. The whole perspective setup can be maintained via the Window menu on top.

• You have access via Window → Open Perspective → Other to allpre-delivered and saved perspectives.

• Please, open Modeler perspective.








Figure 238: Open Perspective

13. To switch easily between different perspectives you can click on the toolbaron top on the corresponding button.

• Each open perspective will be shown here.

Figure 239: Switching Between Different Perspectives









14. For the SAP HANA Studio the central point of Access is the Navigator View,which is usually placed on the left side of the screen.

• In the Navigator tree you can incorporate several SAP HANA instancesdirectly connected with the appropriate user.

• Note that there are two main sections in the navigation tree.

– The Catalog node navigates to the physical tables, views, etc.– The Security node navigates to users and roles.– The Content node navigates to Attribute Views, Analytic Views,

Calculation Views, Procedures and Analytical Privileges

Note: The Content node is only visible inside the Modelerperspective.

Note: Per default the catalog objects are filtered by privileges.

Figure 240: Navigator View

15. The “Catalog” contains all Database schemas.

• Each Schema contains a folder for Column Views, Procedures, Tablesand Views.








Figure 241: Catalog

16. The Folder “Content” contains the Information Model packages.

• Each package can contain a folder for Attribute Views, Analytic Views,Calculation Views, Analytic Privileges and Procedures.

• Open one Analytic View and notice the structure.• Switch between the Semantics, Logical Join, and Data Foundation.

Inspect the Output frame.

Figure 242: Content Folder









17. The Administration console reflects the pre-delivered AdministrationPerspective.

• To get to this screen, choose the Navigate tab followed by a click on the‘administrative’ icon (looks like tools).

• Dependent on your user’s privileges, in this perspective you haveoptions to administrate the SAP HANA Instances.

Figure 243: Administration Console







230Exercise : 2 - SAP BW Tables in SAP HANA

1. In the “Navigator” Tree, expand the node “Catalog”.

Figure 244: Catalog Node

2. Expand the node for the “SAPCIA” schema and then expand the “Tables”folder within that schema.

Figure 245: SAPCIA Schema









3. This shows the first set (1000) of all SAP BW tables in that schema. All BWtables are in HANA!

Figure 246: SAP BW Tables

4. Right-click the “Tables” folder and select Filter from the context menu.This opens a dialog box.

Figure 247: Filter








5. In that dialog box, you can enter a table name.

•Note: You are opening the list of tables within schema“SAPCIA”, so we are searching for tables within the SAPCIAschema.

• Therefore, do not specify the Schema name in the search field.• Enter “/BIC/” in the input field and confirm with OK.

Figure 248: Filter for Tables Dialog Box








233Exercise : 3 - HANA-Optimized DataStore-Object

1. Logon to the BW on HANA system.

Start SAP Logon.

Figure 249: Start SAP Logon

2. Select CIA as your BW system

Figure 250: Select CIA

3. User and password will give by your instructor.








Figure 251: Insert Credentials

4. Use transaction RSA1 and navigate to your InfoArea BW Training → UserArea → Group ##. Create your own DSO.

• Technical name: U##DSO1• Description: U## DSO for Purchase Orders• Use 0EPM_DS01 as a template.

(NULL not O)

Activate your new DSO Object.

You have now created a new standard (non-HANA-optimized) DSO.

Figure 252: Edit DataStore Object

5. Open the “Manage” view for your DSO.









Figure 253: Open Manage

6. Get the table names from your standard DSO. Write down the “table names”.

Figure 254: Contents

7. Open SAPCIA schema in the HANA modeler and find the original DSOtable on DB side. Use the filter dialog to find them.








Active Table

New Data

Change Log (new filter value)

Figure 255: Open SAPCIA Schema

8. Open the table definition and the data preview for you tables to control thecontent.

Figure 256: Open the Table Model

9. Click on the Export SQL icon to display the corresponding SQL statementin the table definition screen. The SQL statement describes the createprocedure for this table.









Figure 257: Export SQL

10. Control the volume of the “Active” table in the “Runtime” tab based onthe “Definition” view.

Your active table has no data records at the moment.

Figure 258: Definition View

11. Back to the BW system, create a dataflow for your DSO object and connectthe DSO with the existing DataSource 0EPM_PO.

Navigate to DSO 0EPM_DS01.

(NULL not O)

12. Use the dataflow copy tool to copy the transformation.








Choose Downwards and No to skip the collection of DTPs and InfoPackages.

Figure 259: Copy a Dataflow

13. Click on Continue for the first steps and choose YOUR DSO U##DSO1 asa target.

Figure 260: Select Your DSO









14. Copy the existing transformation.

Figure 261: Copy the Existing Transformation

15. Start the activation process direct in dialog.

Figure 262: Start the Activation Process

16. Navigate to your DSO U##DSO1. Refresh the tree. Check yourtransformation.








Figure 263: DSD

17. Create a DTP for loading data from the existing DataSource 0EPM_PO intoyour DSO. The DataSource already contains data.

Set the DTP to Extraction Mode Full (to allow for several data loads ofthe same data for comparison between non-HANA-optimized DSO andHANA-optimized DSO).

Figure 264: Create a DTP

18. Start the DTP and check the load process.









Figure 265: Start the DTP

19. Activate your DSO data and check the performance via activation log.

Figure 266: Activate your DSO Data

20. Display the DSO data from HANA side.








Figure 267: Display the DSO Data

21. Now it is time to migrate the “normal” DSO to a HANA optimized DSOobject.

Start transaction RSMIGRHANAD and run the programRSDRI_CONVERT_CUBE_TO_INMEMORY.

Figure 268: /nse38

22. Choose your DSO U##DSO1 and the displayed settings and start themigration process.









Figure 269: Start Migration Process

23. Open DSO Maintenance.

Check Settings. Should be “In-memory optimized” and SID-enabled = “SIDgeneration during activation””. If not SID-enabled:

Check the setting and re-activate DSO

24. Start the DTP again.

Activate the data and check the activation log again.

Nearly zero activation time!!

Figure 270: Log of All Request Operations in DataStore

25. Check the change log data in BW and on HANA side.








Figure 271: Check the Change Log Data

26. Where you can find the Changelog on HANA side now?

It is a “Column View”.

Figure 272: Column View








245Exercise : 4 - HANA-Optimized InfoCubes

1. Create your Cube U##CUBE1 in your own InfoArea U##.

Technical name: U##CUBE1

Description: U## Open Purchase Orders

Template: 0EPM_C01

Activate your new cube.

Figure 273: Create InfoCube

2. Copy the existing transformation based on cube 0EPM_C01.

Figure 274: Copy the Existing Transformation








3. Choose your new cube U##CUBE1 as the target of the transformation andyour DSO U##DSO1 as a source. Activate the transformation

Figure 275: Activate theTtransformation

4. Create a DTP using standard settings and load the data from your DSO intoyour cube

Figure 276: Create a DTP

5. Check the cube model with transaction LISTSCHEMA.

Figure 277: Check the Cube Model









6. Are there real dimension tables?

Figure 278: Call up Schema Viewer for InfoCubes

7. Check the InfoCube tables directly on HANA side. Use the SAP HANAStudio and define a filter for your cube (Schema SAPCIA).

Figure 279: Tables Filter







248Exercise : 5 - HANA-Optimized SPO

1. Create your own DSO-SPO.

Technical name: U##SPO

Description: U## SPO one per quarter

Template: U##DSO1

Mark the check box “Semantically Partitioned”!

2. You want to create HANA optimized DSO objects. Please mark thecorresponding checkbox.

Figure 280: Create HANA Optimized DSO Objects

3. Set field 0CALDAY as a additional key field.

Save the DSO.

Figure 281: Calender Day









4. Select the partitioning field 0CALDAY.

Figure 282: Select the Partitioning Field

5. Add four partitions from 01.2011 to 12.2011 (Quarter of a year).

01.01.2011 – 31.03.201101.04.2011 – 30.06.201101.07.2011 – 30.09.201101.10.2011 – 31.12.2011

Figure 283: Add Four Partitions

6. Start the activation from the wizard.

7. Create the transformation and use your DSO U##DSO1 as a source.








Figure 284: Create the Transformation

8. Complete the transformation and assign 0D_NW_CA to 0CALDAY.

Activate your transformation.

Figure 285: Complete & Activate the Transformation

9. Create a DTP template

Description: U##DTP Template









Figure 286: Create DTP Template

10. Use “DataStore Object” as Data Source and save the template.

Figure 287: DataStore Object

11. Assign your DTP template to all DSO PartProviders. Generate all DTPs.

Figure 288: Assign DTP Template








12. Create a process chain.

Figure 289: Create a Process Chain

13. Assign your four DTPs per drag and drop to your process chain.

Figure 290: Detail View

14. Generate the process chain. Use the default start process and set theparameter for scheduling to “Immediate”.

Figure 291: Generate the Process Chain









15. Move to the process chain maintenance.

Figure 292: Move to the Process Chain

16. Start the process chain and verify the result.

Figure 293: Start the Process Chain







254Exercise : 6 - HANA VirtualProvider

1. Create a VirtualProvider in your InfoArea U## to support direct reporting ona HANA View.

Business Case: Direct reporting on non-SAP data stored in HANA.

Figure 294: Create VirtualProvider

2. Technical name: U##VCUBE1

Description: U## VirtualProvider

Check the radio button Based on HANA Model.









Figure 295: Details

3. Click on button Details and choose

Package: training.general

HANA Analytic View SALES_DATA_001

Figure 296: Click Details Button

4. Choose following InfoObjects direct and add them to the data model tocreate a smart view into the data.








Figure 297: Choose InfoObjects Direct Input

5. Dimension 1

0D_SOLD_TO

0D_MATERIAL

6. Key figures

0D_NETVAL_S

0D_QUANT_B









Figure 298: Key Figures

7. Assign the HANA attributes and key figures to the BW InfoObjects(mapping).

Figure 299: Assign HANA Attributes

8. First the attributes. Please use the F4 value help.








Figure 300: Attributes

9. Second the key figures.

Figure 301: Key Figures

10. Activate your new VirtualProvider. Ignore warning messages about fieldlength.

11. Display data based on RSA1. Select some fields for preview.

Figure 302: Display Data








259Exercise : 7 - TransientProvider

1. Create a TransientProvider for direct reporting on a HANA model via BExor BI reporting without any additional BW content in RSA1.

First, create your own HANA model, creating a copy from an existinganalytic view in HANA studio.

Technical Name: SALES_DATA_##Description: SALES_DATA_##Template: SALES_DATA_001

Figure 303: Create a TransientProvider

2. Save and activate the new view.

Figure 304: Save and Activate New View








3. Switch to the BW system and call transaction RSDD_HM_PUBLISH.

Create a new Analytic Index.

Catalog (package): training.general

SAP HANA Information Model: Analytical View SALES_DATA_##

Click on Create.

Figure 305: Create

4. Confirm the suggestion for naming for the Analytic Index(TransientProvider), i.e., SALES_DATA_##

Figure 306: Analytic Index Naming

5. Save the new TransientProvider in your InfoArea U##.









Figure 307: Save the New TransientProvider

6. Check the new TransientProvider by using a BEx report.

Start the BEx Query Designer: Start → All Programs → Business Explorer→ Query Designer

Figure 308: Start BEx Query Designer

7. Use your BW user and password.Continued on next page







It takes some seconds for the first time.

Figure 309: Use Your BW Credentials

8. Search for your new TransientProvider@3SALES_DATA_##

Hint: If you change something in your Analytic Index or createanother one sometimes you must restart the Query designer forrefresh.

Figure 310: Search for Your new TransientProvider

9. Create and save a query U##_TP1, using your own suggestions for columnsand rows. Test your query via transaction RSRT in BW.








263Exercise : 8 - CompositeProvider

1. Call transaction RSLIMOBW for creating a CompositeProvider.

2. Create a new CompositeProvider. Technical name: U##_CP1

Figure 311: New CompositeProvider

3. Take your Analytic Index SALES_DATA_## and your cube U##CUBE1per drag and drop to the right side.

Use UNION as binding type.

Figure 312: Change CompositeProvider








4. Choose the following fields from your cube (drag and drop)

• Product ID• Order Currency• Gross Order Amount

Figure 313: Field (1)

5. Assign the following fields from your TransientProvider.

Product ID (Map Product ID to Product ID (EPM Demo))CurrencyAmount









Figure 314: Field (2)

6. Change the properties assignment for field Amount.

Figure 315: Change the Properties Assignment

7. Activate your new CompositeProvider and start a data preview.








Figure 316: Activate New CompositeProvider and ignore warningmessages








267Exercise : 9 - DB Connect

1. Create a DB Connect DataSource against HANA DB.

In RSA1, navigate to the DataSources tree for the DB Connect source systemHDB7211.

From the context menu of the application component ZBW_TRAINING,create a new DataSource.

Figure 317: Create a DB Connect DataSource

Technical name: U##_DS1Data type: Transaction DataDescription: U## HANA DBC DataSource

Figure 318: Transaction Data

3. Change to the tab Extraction








Type DB user _SYS_STATISTICS (upper case) and select the HANAinternal table HOST_VOLUME_FILES.

Figure 319: Change to the Tab Extraction

4. Please check all data types that have been assigned by the proposal. Changefour of them according to the screenshot.

Figure 320: TypeContinued on next page








5. Activate the DataSource.

Use the data preview tab to control the access.

You can see the save point files from the HANA DB itself ☺.

Figure 321: Activate the DataSource







270Exercise : 10 - Create WorkspaceUseA BW Workspace is a kind of ‘small sandbox’ which IT defines. IT sets theboundaries, IT sets the amount of resources that a BW Workspace can consumeand exposes some of the central data models to the BW Workspace (data of themodels and their related semantics). The BW Workspace exposes the central datain a logical fashion only. The data is not copied over into the BW Workspace,which means that no data replication is needed.

The goal is to enable the Key Business Users to use this functionality in adedicated and separated environment, which is deeply embedded and integratedin the existing BW landscape. The BW Workspaces bridge the gap betweenthe architected and the departmental data marts. Therefore, Workspaces areintegrated, independent, and they are completely in-memory.

Scenario

Let us assume that you are working as a global sales account manager for acompany, selling computer hardware and corresponding accessories.

In the central enterprise data warehouse, the SAP NetWeaver BW sales data(Purchase Orders) in InfoCubes with a MultiProvider on top.

Additionally, the central SAP NetWeaver BW provides the company’s centralABC Rating information of customers worldwide in an InfoProvider, but you havean own ABC Rating available in a file you would like to use to enrich the centralsales data with your local information and report on the merged data. Moreover,your company has not yet completely integrated the inventory management systemand therefore the SAP NetWeaver BW is not yet supplied with inventory data.

The colleagues from the inventory department provide you with the correspondinginformation (in stock, out of stock, ordered) per product via flat file which youadditionally want to merge with the BW sales data.

In order to keep the scenario simple and focus on the key aspects of thefunctionality we do not consider details like time criteria or joins of key figures,but stick to an easy master data attribute enrichment example.

A BW Workspace has been created for your team by the IT department in theBW Workspace maintenance inside the SAP NetWeaver Business Warehouse.Furthermore, the IT department provided the SAP NetWeaver Business Client andcorresponding roles for access to the BW Workspace Designer.

Procedure1. Open transaction RSWSP. Create your own Workspace.

Technical name: U##_Workspace









Figure 322: Open Transaction RSWSP

2. Assign following settings.

Description: U## First WorkspaceWorkspace Prefix: U##MultiProvider: 0EPM_MP01Maximum Memory: 1 MBMaximum Number ..: 10Master Data Allowed: √

Figure 323: Assign Settings








3. Check the usage for the “Central Provider”. This provider will be the masteror “Central Provider” for further scenarios.

Figure 324: Check Usage

4. Activate the SAP BW Workspace and leave the transaction. Otherwise youlock the workspace.

Figure 325: Activate SAP BW Workspace








273Exercise : 11 - Workspace Designer to Create LocalProviders From A FileUseNow you are in the role as a Business User. You want to use the predefined BWWorkspace. In this Exercise, you will upload your own data to create LocalProviders.

First please copy three files for preparation to your local “Documents” folder

• Business_Partner_Team.CSV• Product_Status.CSV• Business_Partner_ABC.CSV

Naviagte to folder Documents - HANA - BW362. Use user training andpassword hanareadonly for authorization check. Save/Copy these files to yourlocal “Documents” folder.

Procedure1. Open the NetWeaver Business Client to start the BWWorkspace Designer.

Start → All Programs → NetWeaver Business Client 3.5

Hint: The BW Workspace Designer can be started either viathe “NW Business Client” or the “SAP Portal”. If you use theBusinessClient, no Java Stack or SAP Portal installation is necessary.

2. First, establish a connecting to the SAP BW system.

Name: BW on HANAURL: http://wdflbmt7211.wdf.sap.corp:54080/NWBCType: ABAPClient: 003Language: DE or EN







http://wdflbmt7211.wdf.sap.corp:54080/NWBC


Figure 326: Establish Connecting to SAP BW System

3. Logon to BW system by using your BW user account.

User: USER##Passw:“ your new passw.”

Figure 327: Logon to BW System

4. Verify that you are assigned to your workspace “U## First Workspace”(U##_WORKSPACE) by clicking on tab “Workspace Tools”, choose yourworkspace and click on Save button









Figure 328: Verify Your Workspace

5. Click on tab “My Workspace” to create three “Local Providers” based onCSV files.

The first LocalProvider is for the team information. Witch team isresponsible for a customer. They have been stored the data in a local flatfilethat you want to use for the new “Local Provider”.

Click on the Create button

Figure 329: Create Local Providers (1)

6. The source type “File” is correct for your case. Press Continue.









7. Click on Browse to find the flatfile and select Business_Partner_Team.csvfrom your folder Documents.

Figure 331: Browse and Select - Business_Partner_Team.csv

8. Log In for the file system and use the following parameters to load the flat file

• User : training• Password : hanareadonly

Header: 1First Data Row: 2Separator: , (comma!!)Name: U##_BP_TEAMDescription: U## Business Partner TeamClick on Next










9. In the second step choose the data type “Character String with LeadingZeros” for “Business Partner” to fill up the data with leading zeros andchoose Length 10 for the field length.

Click on Upload Data.

Figure 333: Click Upload Data








10. Click on Display Data for checking the data quality.

Now you have created your first local provider.


11. The second LocalProvider is for the ABC rating information. Each customeris assigned to a rating group for internal categorization. They have beenstored the data in a local flatfile that you want to use for the new “LocalProvider”.

Click on Create button

Figure 335: Create

12. The source type “File” is correct for your case. Click Start.









Figure 336: Start

13. Click on Browse to find the flatfile and select “Business_Partner_ABC.csv”from folder “Documents”.

Figure 337: Browse

14. Use the following parameters to load the flatfile:

Header: 1First Data Row: 2Separator: , (comma!!)Name: U##_BP_ABCDescription: U## Business Partner ABCClick on Next








Figure 338: Load the Flatfile

15. In the second step choose the data type “Character String with LeadingZeros” for “Business Partner” to fill up the data with leading zeros andchoose Length 10 for the field length.










Figure 339: Upload Data

16. Click on Display Data for checking the data quality.

Now you have created your second local provider.









17. The third Local Provider includes information about “InventoryManagement”. The standard “Inventory Management” is not in used at themoment and you must upload local information via flatfile.

Click on Create button

Figure 341: Inventory Management Local Provider

18. The source type “File” is correct for your case. Click Start.

Figure 342: Press Start

19. Click on Browse to find the flatfile and select “Product_Status.csv” from yourfolder “Documents”.

Figure 343: Browse and Select Product_Status.csv

20. Use the following parameters to load the flatfile:

Header: 1First Data Row: 2Separator: , (comma!!)Name: U##_P_STATUS









Description: U## Product StatusClick on Next

Figure 344: Load the Flatfile

21. In the second step choose the data type “Character String with LeadingZeros” for “Product” to fill up the data with leading zeros and choose Length10 for the field length.










22. Click on “Display Data” for checking the data quality.

Now you have created your third local provider.


23. At last check that there are three local providers in your workspace. Choose“My Workspace” and tab “Local Providers”.









Figure 347: My Workspace - Local Providers







286Exercise : 12 - Workspace Designer to Create A LocalProvider From A BW DataSource

1. First we need an approval from the BW IT department. They must allowdata access to an BW DataSource.

Switch to the BW System into transaction RSWSP. Edit your BWWorkspace U##_WORKSPACE and sselect the DataSource using Drag &Drop 0EPM_EMPLOYEE as a Central Provider.

Activate your changes.

Figure 348: Select the DataSource

2. Switch to the Workspace Designer in the NetWeaver Business Client.

Create another local provider in your BW Workspace by selecting a BWDataSource as a source.

3. Select the “Employee” DataSource given by the BW Administrator.

Name: U##_LOCAL_DataS

Description: U## Local DataSource Employee (CIACLNT003)









Figure 349: DataSource

4. Confirm the suggestions in the following step and Upload Data.


5. Control your new local provider in your Workspace.








Figure 351: Update BW DataSource








289Exercise : 13 - Workspace Designer to Create ACompositeProviderUseThe next step is to combine the SAP BW data with your own data, based on the“Central Provider” and your “Local Provider”.

Procedure1. Switch to the tab CompositeProviders Click on Create to create a

CompositeProvider.

Figure 352: Create a CompositeProvider

2. In this case we do not need a query as a template. Please click on Startdirectly.

Figure 353: Start

3. Use the following data:








Name: U##_SALES1Description: U## Sales Analysis 1 (local)

Choose all relevant providers (Excluding provider based on BW DataSource)

Click on Next

Figure 354: Next

4. In the next step you must define the relations between the “Central Provider”and your local providers.

The proposal for the relation type “Inner Join” is correct.

Click on “Generate Proposal” for each local provider to choose the right fieldrelation between the “Central Provider” and your locals.

Figure 355: Generate Proposal









5. Choose the default suggestions to analyze and find the proposalsautomatically.

If you want to assign the fields by your own, you can click on the Detailfor Links button.

Figure 356: Choose the Default Suggestions

6. Check the relationships between the “Central Provider” and your localproviders.

1. Table View2. Graphical View








Figure 357: Check Relationships

7. Click on Next.

Figure 358: Click Next

8. Change the field description from “Ctry” to “Country” and check the keyfigure assignments at the bottom of the list.

Ignore warning messages about missing compounding fields.

Click on Next.









Figure 359: Change the Field Description

9. In the following step, you can create a first “default” query for your newCompositeProvider.

Use “Standard” for the query type and confirm the following suggestionsby clickingNext.

Your new query $U##_SALES1 is now generated.

Figure 360: Create Default Query

10. In the last step, please check the model and your settings for a last time.You can display the data, too.

Click on Save and Activate.








Figure 361: Save and Activate

11. Ignore warning messages.

Your CompositeProvider is now ready to use ☺.

Figure 362: Ignore Warning Messages








295Exercise : 14 - Consume CompositeProvider UsingSBO Analysis for MS Excel

1. Open Analysis for Microsoft Excel in your MS Windows menu.

Start → All Programs → SAP BusinessObjects → Analysis for MicrosoftExcel

Figure 363: Analysis for Microsoft Excel

2. Click on tab “Analysis”.

Figure 364: Click Analysis

3. In the next steps you must select your SAP BW system as source.

Click on Insert and choose Select Data Source.








Figure 365: Select Data Source

4. Skip the next popup.

Figure 366: Skip the Next Popup

5. Select CIA (SAP BW system) and click on next.

Figure 367: Select CIA

6. Use your SAP BW user and password.









Figure 368: Use Your SAP BW Credentials

7. Search for your default query $U##_SALES1 and click OK.

Figure 369: Search Your Default Query

8. Define the following row structure.

Figure 370: Define the Row Structure

9. Enjoy your first BW Workspace result ☺!








Figure 371: BW Workspace Result








299Exercise : 15 - Case Study – EPM Model

1. ItelO is an international retail company with several subsidiaries world-widethat buys and sells computers and accessories via a web shop.

It organizes its daily business activities using SAP software. Now, reportingshould be realized using an SAP NetWeaver Business Warehousing solution.As a consultant, you need to design an Enterprise Data Warehousingarchitecture that not only supports the current reporting requirement withgood performance, but also supports the unkown for future reportingrequirements.

Requirement Analysis

In a first step, you have conducted a requirements analysis. As a result younow know that reporting should particularly answer the questions listedbelow. You need to evaluate whether a given reporting requirement belongsto strategic or operational reporting and whether it operates on mass dataor on selective data.

• How much time passes on average per month between a purchase orderand goods delivery? Is there a trend over the years?

• How fast can we deliver after a sales order, dependent on product orsupplier?

• How reliable are our suppliers in terms of quantity, quality, and speedof delivery?

• Turn-over of products on stock: Fast sellers, slow sellers?• Current stock per product, i.e. product availability?• Sales revenue per employee, per customer, per product, per region in

different time periods (week, month, quarter)?• Total weight and volume of goods delivered per city and month?• Sales quantity in pieces per product and week?• Status of sales order?• Outstanding invoice amounts?

Business Process and Source Data Analysis

In a second step, in order to get an overview of the business process andavailable source data, you have asked IT to provide you with the necessaryinformation on the business model and its implementation on ERP side.They give you the following list:








Master Data

• Product: Main table SNWD_PD, DataSource 0EPM_PROD• Employee: Main table SNWD_EMPLOYEES, DataSource

0EPM_EMPLOYEE• Business Partner: Main table SNWD_BPA, DataSource 0EPM_BP• Organizational Structure: SNWD_COMPANY and

SNWD_ITELO_DEPTS

Transaction Data

• Purchase Order: main tables SNWD_PO and SNWD_PO_I,DataSource 0EPM_PO

A purchase order has five different status tags:

1. Approval Status (initial, approved, rejected)2. Confirmation Status (initial, confirmed, sent, cancelled)3. Lifecycle Status (closed, new, in progress, rejected, cancelled)4. Order Status (initial, delivered)5. Invoicing Status (initial, invoiced)

• Purchase Order Invoice: main tables SNWD_PO_INV_HEAD andSNWD_PO_INV_ITEM

• Sales Order: main tables SNWD_SO and SNWD_SO_I• Sales Order Invoice: main tables SNWD_SO_INV_HEAD and

SNWD_SO_INV_ITEM• Storage Bin: main table SNWD_STOCK








301Exercise : 16 - Design LSA for Case Study

1. Create a draft of the BW architecture for transaction data only to realize therequirements from the case study under consideration of the LSA principlesusing the data flow modeling tool.

InfoArea: BW Training → User Area → Group ## (T_BW → T_USERS→ U##)

Technical name: U##_DF_EPMDescription: U## Data Flow EPM case study

It is sufficient to use object templates, since we are not going to implementthe complete scenario. The purpose is to design the Enterprise DataWarehousing Architecture.

When sketching your architecture, feel free to use all the availableInfoProvider types to represent the different layers, and also keep in mind thatlogical partitioning can contribute to a good performance. Where adequate,you may incorporate the existing InfoProviders, DataSources, and data flows.







302Exercise : 17 - LSA → LSA, powered by SAP HANA

1. Inspect your LSA for the Enterprise Procurement Model from the previousUnit. A technical migration to SAP NetWeaver BW, powered by SAPHANA has been conducted.

1. Which steps do you have to undertake as a minimum from anapplication point of view?

2. Where do you expect performance improvements and why?3. How can you streamline your Enterprise Data Warehouse to arrive at

a consistent flexible EDW core?









2. Solution:

1. Migrate InfoCubes, DSOs, and SPOs to HANA-optimized objects.2.

• Load performance (DSO activation, update InfoCubes noDIM-IDs).

• Query performance: Reading from columnar tables in memoryis much faster and evaluation of aggregations and calculations isdone using the HANA engine.

3. Inspection of the Business transformation Layer transformations shows:

• For Sales Orders: Quantity Conversion takes places. If this canbe moved to the query - because the result needs not be storedpermanently – the Sales Order InfoCubes (or Infocube-SPO) canbe deleted. The Sales Order MultiProvider then sits directly onthe Propagator DSO-SPO.

• Purchase Orders: The Order Lifecycle Status is determined usinga routine. Thus, the transformation is necessary and the InfoCubescannot be deleted.

• Invoices: The transformationen are only 1:1. The InfoCubes (orInfoCube-SPOs) can be deleted.







304Exercise : 18 - LSA, powered by SAP HANA → LSA++(Optional)

1. Throughout the course, you have created a number of InfoProviders foryour version of the Enterprise Procurement Model (EPM) Enterprise DataWarehouse. Into which LSA++ layer would you file your BW objects?Which reporting scenario does the InfoProvider support?

1. VirtualProvider: U##VCUBE1, U## VirtualProvider

Solution: Open ODS Layer. Sales data in realtime. Could be combinedwith sales data reporting in EDW core to report on both historic dataand agile current data.

2. TransientProvider: @3SALES_DATA_##, SALES_DATA_##

Solution: Same as for VirtualProvider but less integration with BWdata model, because transient InfoObjects are used without mapping toexisting BW InfoObjects.

3. CompositeProvider: U##_CP1, U## CompositeProvider

Solution: Agile Data Mart Layer. Union of Open Purchase Ordersdata from InfoCube (EDW core; architected data mart layer) with agilesales data from TransientProvider (open ODS layer). The way theCompositeProvider is built does not conform to best practice, since theInfoCube is directly used. According to best practice, the InfoCubeshould be wrapped in a MultiProvider (virtual wrap layer). Then, theCompositeProvider should be created on top of the MultiProvider andthe TransientProvider (virtual composition layer).

4. DB Connect DataSource: U##_DS1, U## HANA DBC DataSource

Solution: Open ODS Layer. All DataSources reside in the open ODSlayer that serves as the LSA++ successor of the data acquisition layerin LSA. Since we do not know how the data will be consumed, thereporting scenario cannot be specified at this stage. It may be possible tocreate a VirtualProvider based on a DTP with direct access or to utilizethe DataSource as the first object of an EDW core staging process.

5. Local Provider:

• U##_BP_TEAM, U## Business Partner Team• U##_BP_ABC, U## Business Partner ABC• U##_P_STATUS, U## Product Status









Solution: BW Workspace Layer. Additional departmental local masterdata that enhances the business partner master data and the productmaster data are uploaded into BW and may be accessed by membersof the department.

6. CompositeProvider: U##_SALES1, U## Sales Analysis 1 (local)

Solution: Virtual Composition Layer. The Central Provider – of theBWWorkspace that has been used – is a MultiProvider that serves as awrap on top of an InfoCube holding Open Purchase order data (EDWcore; architected data mart layer). It is combined with an inner join tolocal data from the Local Providers within the given BW workspace(BW Workspace layer). This supports departmental reporting, wherecorporate data shall be enhanced with local data that are of relevanceonly for a given single department: “I want to enhance the BW reportwith my own Excel data.”







306Exercise : 19 - Optional: LSA++, Evaluation ofAdditional Reporting Scenarios

1. How would you incorporate the following scenarios into your LSA++?

1. For a special marketing campaign in Italy, Spain, Greece, and Turkey,the products delivered have been enhanced with local give-aways. Alist has been manually created which type of give-away has been packedto which sales order delivery. The local sales executives now want toknow, whether the time between two sales orders of their customershas been reduced in the month after the campaign as compared tothe months before the campaign, to evaluate the effectiveness ofthe campaign. In addition, they want to know whether the type ofgive-away has had an influence on customer behaviour.

2. Your Bangalore-based company has sales agencies in almost allcountries of the world. However, in most countries, the number ofsales workforce is very small, so that a few employees cover the wholecountry. Only the Indian market is large enough to split the countryinto sales regions. According to corporate reporting guidelines, thecorporate sales reports only report on country level. Consequently, theflexible consistent EDW core uses the country as its most granulargeographic InfoObject. For the Indian market, sales reporting should bepermanently enhanced by incorporating the Indian sales region into themodel, without remodelling the central EDW core so as to not affectreporting in all other countries.

3. The Chinese New Year is approaching. Since in the US market, manycustomers of the ITelO Company are of Chinese background, the localSales department has conducted a text pattern search on the names ofall US customers. The external text mining tool returned all customerswhose names suggest a Chinese background as a CSV file. A mailinghas been delivered to this group of customers, suggesting an ITelOproduct as a gift for Chinese New Year. Now the sales executive wantsto analyse the effect of the campaign by comparing the sales volumesfor the group of “Chinese” customers this year with the previous yearas well as the sales volume per customer for the group of “Chinese”customers versus “non-Chinese” customers.








Lesson Summary

You should now be able to:• SAP BW on HANA






Unit Summary BW362

Unit SummaryYou should now be able to:• SAP BW on HANA







BW362 Course Summary

Course SummaryYou should now be able to:

• Explain the BW on HANA Landscape.• Differentiate between HANA-Optimized Datastore Object and standard

BW Data Store Object.• Differentiate between HANA Optimized Info Cube and standard BW Info

Cube.• Explain the consuming of HANA models.• Describe BW powered by HANA.• Working with BW Workspace in the HANA environment.• Explain the Layered Scalable Architecture without SAP HANA.• Explain the new functionalities of Layered Scalable Architecture with SAP

HANA.






Course Summary BW362







Appendix 1Analyze Requirements for the Case Study

1. Read through the case study (Section 6.2) and get an overview of the wholescenario. Do not spend too much time on the details, simply try to summarizethe requirements and obtain an overview. Create a list of keywords in orderto categorize and describe the requirements.

____________________________________________________________

____________________________________________________________

____________________________________________________________

____________________________________________________________

____________________________________________________________

2. Which points do you think still need to be clarified?

____________________________________________________________

____________________________________________________________

____________________________________________________________

____________________________________________________________

____________________________________________________________

3. Inspect the available source data using transaction SE16 for the tableslisted in the case study. Inspect the available BW Content in InfoArea0D_NW_DEMO_EPM (E-Procurement Management Modell (NWDemo EPM)) and application component 0EPM (Enterprise ProcurementModel).

____________________________________________________________

____________________________________________________________

____________________________________________________________






Appendix 1: Analyze Requirements for the Case Study BW362

____________________________________________________________

____________________________________________________________

4. Can the delivered BW Content be used as it is to support the reportingrequirements? What is missing?

____________________________________________________________

____________________________________________________________

____________________________________________________________

____________________________________________________________

____________________________________________________________







FeedbackSAP AG has made every effort in the preparation of this course to ensure theaccuracy and completeness of the materials. If you have any corrections orsuggestions for improvement, please record them in the appropriate place in thecourse evaluation.




