OBIEE ARCHITECTURE

Presented byARC

BI

Degree of Intelligence

Com

petit

ive

Adv

anta

ge

How many, how often, where?Ad hoc reports

Query/drill down

Alerts

Statistical analysis

Forecasting/extrapolation

Predictive modeling

Optimization

Standard reports What happened?

Where exactly is the problem?

What actions are needed?

Why is this happening?

What’s the best that can happen?

What if these trends continue?

What will happen next?

Analysis

Accessand

Reporting

DATAINFORMATI

ONKNOWLEDG

EINTELLIGENC

E

Raw

BasicArchitecture of OBIEE

Client Presentation Services

BI Server

BI Scheduler

Repository

OO

Oracle

SAP

Siebel

Data Sourc

eData Source

Functional Architecture

Technical Architecture

System components are still C/C++ executable and are controlled by OPMN and managed by Fusion Middleware Control

Java Components are J2EE applications and are usually installed in the managed server and controlled by Fusion Middleware Control.

SYSTEM AND JAVA COMPONENTS

• Its adopted to start, stop and monitor processes across system components (BI Server, BI Presentation Server, BI Scheduler and BI Cluster Controller).

• You can either access OPMN through the command line (opmnctl), or Oracle’s recommended approach is to use a graphical interface within Fusion Middleware Control.

• OPMN is also used in the 11g stack to control Essbase, Discoverer and other BI components, so it’s a tool that’s worth learning

Oracle Process Manger and Notification Server(OPMN)

Manage System Components (BI Server, BI Presentation Server etc)

Start, Stop and Restart all System Components and Managed Servers

Configure Preferences and DefaultsScale out System ComponentsPerformance Monitoring and Diagnostics

Oracle Enterprise Manager Fusion Middleware Control

Users queries via the Presentation Server

The Oracle BI Server converts these queries to physical SQL/MDX, via the Oracle BI Repository

Queries are passed to the underlying physical databases and OLAP cubes

Data returned to users in the form of dashboards and reports

Caching oracle BI Framework

CachingWeb Server: Oracle Analytics’ Web Server caches

queries and query results. When a user submits a query, the web server examines the logical SQL to see if it matches an existing cached query. If it does, then the Web Server uses the results without re-submitting logical SQL to the Oracle BI Server.

Database Server: The Oracle BI Server also allows queries that

require extensive database processing to be pre-scheduled to run so that results are already available when users open their dashboards.

OBIEE Security: Repositories and RPD File Security It contains all the metadata, security rules,

database connection information and SQL used by an OBIEE application.

The RPD file is password protected and the whole file is encrypted.

Only the Oracle BI Administration tool can create or open RPD files and BI Administration tool runs only on Windows.

Security

Data level security: This controls the type and amount of data that you can see in a report. 

Object level security: This provides security for objects stored in the Web Catalog, such as dashboards, dashboard pages, folders, and reports. (Web object security) or subject areas

User level Security User-level security refers to authentication and confirmation of the identity of a user based on the credentials provided.

Infrastructure & Management

Database

Middleware

Applications

Repository (RDP) File Define OBIEE Solutions

.rpd file

The physical layer:

Represents the physical structure of the data sources to which the Oracle BI Server submits queries.

Represents the actual tables and columns of a database/data source. 

• It also contains the connection definition to that database, or data source.

•  join definitions including primary and foreign keys.

.rpd contn..Business Model mapping:

This is where business logic is added in to the mix in the form of formulas. 

The business model simplifies the physical schema and maps the users’ business vocabulary to physical sources.

Your aggregation rules are defined here as well. 

Traversing a Request to SQL

Approaches to OLAP ServersThree possibilities for OLAP servers(1) Relational OLAP (ROLAP)(2) Multidimensional OLAP (MOLAP)(3) Hybrid OLAP (HOLAP)

ROLAP: Dimensional Modeling Using Relational DBMSRelational and specialized relational DBMS to store

and manage warehouse data/OLAP supported on top of a relational database.

Special schema design: star, snowflake

Special indexes: bitmap, multi-table join

Proven technology (relational model, DBMS), tend to outperform specialized MDDB especially on large data sets

ProductsIBM DB2, Oracle, Sybase IQ, RedBrick, Informix

Points to be noticed about ROLAPDefines complex, multi-dimensional data with

simple modelReduces the number of joins a query has to

processAllows the data warehouse to evolve with rel.

low maintenanceCan contain both detailed and summarized

data.ROLAP is based on familiar, proven, and

already selected technologies.BUT!!!SQL for multi-dimensional manipulation of

calculations.

MOLAP: Dimensional Modeling Using the Multi Dimensional ModelMDDB: a special-purpose data modelSpecialized data structures • Multicubes vs HypercubesArray-based storage structuresDirect access to array data structuresSometimes on top of relational DBProducts

Pilot, Arbor Essbase, Gentia

Points to be noticed about MOLAP

Pre-calculating or pre-consolidating transactional data improves speed.

BUTFully pre-consolidating incoming data, MDDs require an enormous amount of overhead both in processing time and in storage. An input file of 200MB can easily expand to 5GB

MDDs are great candidates for the <50GB department data marts.

Rolling up and Drilling down through aggregate data.

With MDDs, application design is essentially the definition of dimensions and calculation rules, while the RDBMS requires that the database schema be a star or snowflake.

Hybrid OLAP (HOLAP)HOLAP = Hybrid OLAP:

Best of both worlds

Storing detailed data in RDBMS to optimize time of cube processing

Storing aggregated data in MDBMS for fast query performance

User access via MOLAP tools

Vertical partitioning In this mode HOLAP stores aggregations in MOLAP for fast query performance, and detailed data in ROLAP to optimize time of cube processing.• Horizontal partitioning In this mode HOLAP stores some slice of data, usually the more recent one (i.e. sliced by Time dimension) in MOLAP for fast query performance, and older data in ROLAP.

Multi-dimensional access Multidimensio

nal Viewer

RelationalViewer

ClientMDBMS Server

Multi-dimensionaldata

SQL-Read

RDBMS Server

Userdata Meta data

Deriveddata

SQL-Reach

Through

SQL-Read

Data Flow in HOLAP

When deciding which technology to go for, consider:

1) Performance:

How fast will the system appear to the end-user?

MDD server vendors believe this is a key point in their favor.

2) Data volume and scalability:

While MDD servers can handle up to 50GB of storage, RDBMS servers can handle hundreds of gigabytes and terabytes.

BI ARCHITECTURE

Information Sources Data Warehouse Server(Tier 1)

OLAP Servers(Tier 2)

Clients(Tier 3)

OperationalDB’s

SemistructuredSources

extracttransformloadrefreshetc.

DataWarehouse

e.g., MOLAP

e.g., ROLAP

serve

OLAP

Query/Reporting

Data Mining

serve

serve

THANK YOU