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Page 1: Data treasure – thar she blows! · Data treasure – thar she blows! Heave ho your SAP data treasure with Data Analytics ... delivers comprehensive real-time analysis results and

Data treasure – thar she blows! Heave ho your SAP data treasure with Data Analytics

it-novum.com

Page 2: Data treasure – thar she blows! · Data treasure – thar she blows! Heave ho your SAP data treasure with Data Analytics ... delivers comprehensive real-time analysis results and

Data Analytics makes more of your SAP data

A wealth of data that is hard to mine The SAP treasure down in Davey Jones‘ locker

„Thin“ data

Sailing the seas of SAP

Some alternatives are (not) a solution Numbers are limitless – but Excel isn‘t

Non-standardised solutions – will run you aground

Full speed ahead with SAP experts

How the digitally gifted can help Turning lead into gold

Looking back helps forge the way ahead

Blowing hot and cold?

Don‘t let the pirates make off with your treasure

Pentaho – The first among equals

Data recovery using the Hitachi Data Connector for SAP ERP

and Business Warehouse Data integration – SAP ERP table input step, SAP BW infocube input

Data blending – SAP BW/ERP RFC executor

Data offload – SAP BW DSO input step

Overview

Glossary

4

5

7

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Contents

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it-novum GmbH Germany Headquarters Fulda: Edelzeller Straße 44 ● 36043 Fulda ● Phone: +49 (0) 661 103 333 Branches in: Dusseldorf and Dortmund it-novum branch Austria Austellungsstraße 50 / Zugang C ● 1020 Wien ● Phone +43 1 205 774 1041 it-novum GmbH Switzerland Hotelstrasse 1 ● 8058 Zurich ● Phone +41 (0) 44 567 62 07

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Overview

More than 300,000 companies in 190 countries use

an SAP solution as their ERP system. And 75% of all

transaction revenues worldwide are generated via SAP.

Thus it‘s easy to see that SAP is by far the most widely

used ERP software in the world. The following review

therefore focuses on scenarios where an SAP system

is in use – although many of the statements and no-

tes can also be applied to other ERP systems. Analysing

SAP data reveals interrelationships and trends and can

provide management with valuable decision-making

support when setting the company‘s strategic agenda.

Also, using a professional business intelligence program

delivers comprehensive real-time analysis results and

allows data from different sources to be mixed together.

Various software tools are available on the market to

access SAP system data.

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it-novum Heave ho your SAP data treasure

1 Data Analytics makes more of your SAP data – two practical examplesAre all the decision-makers in every company really aware of the possibilities offered by the data that is available in their company? For example, companies typically hold a wide variety of information about each of their customers. In ad-dition to contact data, all information regarding the company‘s commercial pro-cesses is also available. But the company‘s software is also used for project and supplier controlling, so how can this data be used beyond just simple business processing? Well, quite simply, by linking them together in a meaningful way.

Here‘s an example: The automotive supplier BOS has branches in Europe, North America and Asia. Until recently, there was no uniform controlling solution across the entire commercial group. Each site used a different application, and most were developed in-house. The relevant data was sent in Excel sheets to the head office, where this information was then analysed manually. The usual problems of an Excel-based solution soon emerged: data fragmentation and a susceptibility to errors. In addition, the meaningful value of the analyses was limited. Creating reports and other visualisations was also cumbersome and time-consuming, as these had to be programmed directly in Java. BOS has since remedied this situa-tion: It now uses the Pentaho Data Analytics platform for evaluating the SAP data from across its entire group of companies. Management can now easily display the information for each unit at the simple push of a button.

Consequently, the company‘s controlling efficiency and the informational cont-ent of its data analyses has increased significantly.

But much more can be done with the information drawn from the SAP system by bringing together the company‘s figures with data from outside the ERP system.

Here‘s another example: Rhein-Sieg Abfallwirtschaftsgesellschaft (RSAG) is responsible for waste disposal and recycling for 19 municipalities and 600,000 re-sidents with a central task here being materials management. Here, all incoming and outgoing materials – such as residual waste, paper and bulky waste – are tracked according to origin or disposal company. The company uses the indust-ry-wide solution TRAS, which also organises storage facilities and coordinates the routes of the collection vehicles.

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it-novum Heave ho your SAP data treasure

Until recently, all recycling centres and landfills sent their TRAS data individually to RSAG headquarters. There, the figures were included in their corresponding Excel tables. In order to generate Excel reports for managing the business, the employees had to struggle with the difficulties already mentioned above. Also, TRAS doesn‘t provide any commercial key metrics. Information on the vehicle costs involved in collections operations, for example, can be found in RSAG‘s SAP program. Getting meaningful and timely evaluations of the data from both infor-mation sources was just not feasible. These difficulties are now, however, a thing of the past: With the Pentaho Data Analytics platform, RSAG now relies on a uni-form reporting system based on a consolidated data basis. RSAG can now draw additional insights and findings from its systems, as the data is always available – because they can now link up data from TRAS, their industry-level software, with that from their SAP system.

2 A wealth of data that is hard to mineIf you dive down into the depths of an SAP system, your view quickly becomes murky. This makes it almost impossible for non-SAP specialists to obtain the relevant data they need and then comprehensively analyse it with a Data Ana-lytics tool.

2.1 The SAP treasure down in Davey Jones‘ locker

Pulling your SAP treasure aboard, out of these murky depths, is not easy, becau-se it‘s bulky: That is, it‘s in a proprietary format. The data cannot be grasped intuitively and must first be found and then correctly identified. Let‘s be honest: Who other than an SAP expert knows that the SAP abbreviation „MATNR“ stands for the Material number table field or that you need to use „SPRAS“ to find the Language key table field?

The storage structure of SAP data also differs fundamentally from the structure used in a data warehouse (DW). SAP data is transaction-oriented. Finally, the ERP system is used to manage ongoing business processes, while the DW supports data analysis and establishing a reporting system and dashboards. Without ha-ving the appropriate SAP specialists, a company will find it difficult to address the right SAP levels to access data.

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2.2 „Thin“ data

Another difficulty is that the informational content of SAP data is often too low for in-depth analyses. The SAP system of course displays the sales volume of a custo-mer X in time period Y for goods Z. However, if you also want to know whether the sale of goods has altered when a supplier has been changed, SAP quickly reaches its limits. And if you need to link to a CRM system, for example, so that you can evaluate the influence of a mailing campaign on sales development, this just isn‘t possible.

2.3 Sailing the seas of SAP

Raising your SAP treasure chest is resource-intensive: Analytical evaluations tie up a lot of computer capacity due to the amount of data that has to be processed. The ERP system should therefore not be weighed down with these processes. Otherwise, computer processes could slow down – and in a worst-case scenario, the capacity can even be maxed out, causing things to hang. Plus, SAP data ch-anges constantly as a part of ongoing business operations. This becomes proble-matic if the same analysis needs to be called multiple times.

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3 Some alternatives are (not) a solution

3.1 Numbers are limitless – but Excel isn‘t

Excel is the world‘s most widely used spreadsheet program and continues to enjoy great popularity when it comes to analysing company data. Data proces-sing in Excel, however, requires a great deal of personnel and time, considerable susceptibility to errors due to manual data transfer, data fragmentation and very limited evaluation options. In addition, there is the question of how secure data is in Excel tables. And last but not least, Excel offers neither sophisticated visuali-sation nor automated reporting.

3.2 Non-standardised solutions – will run you aground

Stand-alone solutions are just as popular as Excel – and just as inappropriate: This results in every department, every branch, every subsidiary building its own data analysis program. This approach is not only highly inefficient, it also deprives users of a view of the big picture, because only the data in each respec-tive department is recorded and evaluated. Homebrew evaluation tools should, therefore, be reserved for tinkerers living on their own lonely little islands and not used by business professionals.

3.3 Full speed ahead with SAP experts

SAP experts would know how to overcome many of the existing hurdles. So why not just hire more of them? Well, for one thing, currently there isn‘t exactly a glut of them on the labour market. Also, there is a risk that knowledge will be lost to the company within a short period of time when employees leave. Moreover, it cannot be ruled out that some SAP professionals may have the ERP system rather than the required data analysis in mind.

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4 How the digitally gifted can helpData Analytics programs are electronic Einsteins, because with them data can be extracted from the SAP system, processed, evaluated, integrated in a user-friend-ly form and then integrated with data from other enterprise systems. As soon as the data is available in the Data Analytics system, you can get started:

4.1 Turning lead into gold

The first step is data enhancement. Individual SAP data has very limited informa-tional content. Only by enriching this information – that is, linking it with other as well as non-SAP data – does it take on the informative value necessary for analy-sis purposes. Thus, turning lead into gold. The non-SAP systems can be any of the applications used in the company: CRM, PPS, HR, MIS and DM systems, helpdesk, online shop, sensor data, industry-specific solutions, geo data and much more.

4.2 Looking back helps forge the way ahead

Data is constantly growing as a natural part of business operations. In order to avoid slowing down processing or constantly having to expand computing capacities, it makes sense to store information that is currently no longer requi-red somewhere else. Deleting it is not an alternative. And of course, certain data must be archived by law. In addition, the available historical knowledge can help to evaluate developments retrospectively and make strategic decisions for the future. It is therefore advisable to store the historical data in a data warehouse or data lake. In this way, you have access to the data when you need it, but it doesn‘t place a burden on your daily processes.

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4.3 Blowing hot and cold?

Evaluations are not created every day. After all, analyses aim to provide manage-ment with well-founded insights and forecasts that support them in their tactical and strategic decisions. Data evaluations must therefore be carried out according to a defined standard in order to provide reproducible results. Data Analytics software guarantees this reliability.

4.4 Don‘t let the pirates make off with your treasure

The importance of protecting your company‘s data and strategic considerations should not only be known by every manager, but also by every employee. This makes it all the more astonishing how carelessly this wealth of knowledge is often handled. Data Analytics software puts a stop to abusive access to analysis data. By using a corresponding rights system, no unauthorised person can access the information. Manual evaluations – in the form of Excel tables, for example – can-not do this.

Video

„Evaluate and visualize SAP data with a mouse click“

Watch here!

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5 Pentaho – The first among equalsSince 2007, Pentaho has been one of the most important platforms for Data Analytics applications. It has proven itself time and again in the areas of data integration, data analysis, data mining, data visualisation and reporting in the big data environment. Dashboards and Mobile Data Analytics are now considered standard. And thanks to its open architecture, Pentaho can be integrated har-moniously into the existing IT landscape. In addition, over the years a separate community has been established, there are user forums and blogs, and regular user meetings also take place.

Compared to other Data Analytics tools, Pentaho has two decisive advantages: the open-source version is very powerful and allows unlimited testing of the software using all its functionality. Pentaho also has a modular structure. This allows you to use individual components without – as is the case with many other solutions – having to install the entire suite. One component is Pentaho Data In-tegration (PDI). It is one of the most powerful ETL tools on the market. PDI is used to migrate data and build a data warehouse with connectivity to other databases so that complex analyses can be performed.

To combine SAP data with Pentaho Data Integration and to connect this then with other data sources, various tools are available, such as a web services Lookup step, Open Hub Service and Enterprise Services (e.g. web services). Their use is sometimes quite complex: Customer-specific adaptations are required and spe-cial transformations have to be written. Connectors are available, but these have not been updated for some time. They are, therefore, useless with newer Pentaho versions. To enable SAP users to enjoy the advantages of Pentaho‘s data analy-sis, it-novum‘s experts, partners and service providers for all aspects of Pentaho, have decided to develop their own solution: the Hitachi Data Connector for SAP

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6 Data recovery using the Hitachi Data Connector for SAP ERP

and Business Warehouse

The Hitachi Data Connector for SAP ERP and Business Warehouse has an easy-to-use interface for processing SAP data with Pentaho Data Integration. The follo-wing SAP steps are supported:

▶ SAP ERP Table Input

▶ SAP BW/ERP RFC Executor

▶ SAP BW DSO Input

▶ SAP BW Infocube Input With the Hitachi Data Connector for SAP ERP and Business Warehouse, applica-tion scenarios and use cases – such as onboarding, blending or offloading of SAP data – can be implemented easily and cost-effectively. It can read all data from all SAP modules (e.g. FI, CO, MM, etc.). Plus, the connector uses RFC function modules (BAPIs) and SAP tables. Both complex and nested SAP structures as well as structures and data that only exist at runtime in the SAP system can also be queried.

Access to data from SAP BW is possible using two different scenarios: First, the data from the staging area can be extracted by accessing SAP Data Store Objects (DSO), and second, the Connector can use analytical workloads (querying) to ac-cess the data warehouse layers (SAP Infocubes). Pentaho makes the results of the data analysis available at the push of a button. Automation significantly reduces manual tasks and allows management to retrieve any analysis in a fraction of an instant.

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6.1 Data Integration

During data integration, the SAP data is first converted into a user-friendly format and stored in the staging area. The Connector accesses the metadata stored in SAP and provides the user with both the technical field description and the cor-responding functional input. it-novum has placed special emphasis on user-fri-endliness: Both the display of the database fields and the preview function can be configured to suit the user‘s needs. Among other things, the user can create a filter that is then sent along with a table retrieval and executed in the SAP system. Historical data is stored in a logical structure in the data warehouse that can be easily comprehended by the user.

6.2 Data blending – SAP BW/ERP RFC executor

This is where SAP data is merged with data from other systems. These are not just different data sources: The file formats and data types can differ, too. For examp-le, it‘s possible that SAP data could be linked with a NoSQL database in order to increase the significance of KPIs through the use of contextual information. The processed data is used for both descriptive and prescriptive analyses. It is also possible to call SAP function modules that you have written yourself, such as BAPI modules. It is even possible to link several function blocks together. The connec-tor can also access BW-specific data structures such as Infocubes and DSO.

6.3 Data offload – SAP BW DSO input step

In order to avoid higher licensing costs with an increasing volume of data and so as not to push the computing system to its limits, the data is classified into hot, warm and cold data according to its volume and access frequency. Data is classi-fied as hot when it is in constant use. In normal business operations this would be a rather small amount of information. Most information would be classed as cold data: data that is only needed sporadically. This should therefore be stored on suitable platforms outside the ERP system, e.g. in Hadoop, which is exactly what the corresponding Connector module makes possible.

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7 OverviewWith the Hitachi Data Connector for SAP ERP and Business Warehouse, SAP data can be cost-effectively and independently evaluated using the Pentaho analytics platform. It has state-of-the-art functionality and it-novum is continuously expan-ding it for use with further SAP steps.

Additional information about the Connector is available free of charge on the Internet:

▶ https://it-novum.com/big-data-analytics/pentaho-sap-connector/

▶ https://www.youtube.com/watch?v=nMqBZnjHdUQ&index=8&list=PLF2lSFw-

VOYNuoLm5JMVR8PRNUjtIcGmfv

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8 Glossary

▶ BAPIs Business Application Programming Interfaces: Business objects in SAP that allow external programs to access SAP data and processes.

▶ BW SAP Business Warehouse, the SAP data warehouse application.

▶ Dashboard Visualisation tools that display data such as KPIs and metrics and produces them using graphical evaluation systems such as traffic lights or scales.

▶ Data Blending Data merging: Data from different sources is combined with each other.

▶ Data Integration Data from different sources, usually with different data structures, is transferred into a common, uniform data structure.

▶ Data Lake Unlike a data warehouse, a data lake stores raw data as it is provided by the data source. It can be in a structured or unstructured form.

▶ Data Offload Offsite data storage.

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▶ Data Warehouse (DW) Data Warehouse is a central database in which data from several sources is combined and aggregated for use in reporting and data analysis.

▶ DSO Operational Data Store: A database for the integration of data from different data sources so that this can be promptly evaluated. This is normally either not possible or can only be done with difficulty using the source systems.

▶ ETL ETL stands for Extract Transform Load. This is a processing process for setting up and further developing a data warehouse.

▶ Infocubes or just „Cubes“ A self-contained dataset stored in the SAP system that is used for analyses and reports.

▶ RFC Remote function calls enable external access to BAPI function modules.

▶ Staging Area After the data has been extracted from the data sources, it is collected, buffered and transformed in the staging area. The processed data is then transferred from the staging area to the target database (load).

▶ Transaktionsorientiert Designed for process handling.

▶ VBRP SAP table for storing billing documents (Accounting).

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it-novum Profile

Why you should speak with it-novum... We are leveraging these business intelligence and big data benefits to businesses:

▶ 360-degree view of your customers ▶ Specialist departments evaluate Big Data data themselves thanks to self-service analytics ▶ Identification of new revenue sources through intelligent use of company data ▶ Cost savings through the use of a data warehouse ▶ Avoiding the time-consuming and error-prone Excel mess

If you want to use these benefits in your business, we should get to know each other!

it-novum offers extensive services for your big data analytics project:

▶ Data engineering ▶ Implementation of data warehouses and data lakes ▶ Hitachi Data Connector for SAP ERP and Business Warehouse for processing SAP data ▶ Pentaho/HVA Connector for video stream analytics ▶ Predictive analytics and machine learning ▶ Dashboards and data visualization ▶ Embedded analytics

Leading in Business Open Source solutions and consulting

it-novum is the leading IT consultancy for open source based business solutions in the German- speaking market. We operate from our main office in Fulda and branch offices in Dusseldorf, Dortmund, Vienna and Zurich to serve medium and large enterprises as well as the public sector.

As Hitachi Vantara Preferred Partner for Big Data Insights and IoT we are experts in using Pentaho. With our expertise in consulting, training and support we help companies to generate insights from their data and to make their data-driven projects successful

Your contact person for Big Data Analytics: Stefan Müller Director Big Data Analytics [email protected] +49 (0) 661 103 942

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it-novum Contact

it-novum.com

Andreas Kuhn Sales Manager Big Data Analytics [email protected] +49 (0) 661 103 363

Johannes Michael Weiß Country Manager [email protected] +43 1 205 774 1041

Stephan Köpfli Country Manager / CEO [email protected] +41 (0) 79 652 51 60

For Germany:

For Austria:

For Switzerland:

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