OBIEE - E2 - Architecture

8/7/2019 OBIEE - E2 - Architecture

1/27

OBIEE Architecture


2/27

August 4, 2011

Prerequisites*

What is Business Intelligence? What are BI needs and challenges?

What is Data Warehousing?

What are the traditional ways to organize Data?

What is the difference between Transactional andAnalytical Systems?

What is a Dimension / Fact / Star Schema?

What are various available BI tools in the industry?

* Should have covered by E0 and E1 levels


3/27

August 4, 2011- 3 -

OracleBI Server

ProactiveDetection

and Alerts

DisconnectedAnalytics

Ad-hocAnalysis

MS OfficePlug-in

Reporting &Publishing

InteractiveDashboards

OLTP & ODSSystems

Data WarehouseData Mart

SAP, OraclePeopleSoft, Siebel,

Custom Apps

FilesExcelXML

BusinessProcess

Multidimensional Calculation and Integration Engine

Intelligent Caching Services

Simplified Business Model and Abstraction Layer

Intelligent Request Generation and Optimized Data Access Services

WebServices

Multi-DimensionalSources

OBIEE - Unified Business Intelligence Infrastructure

Advantages:

Consolidate and

standardize BI tools

Seamless user

experience across

products

Unified metadata

and shared

services
http://www.microsoft.com/nethttp://java.sun.com/


4/27


5/27


6/27


7/27

August 4, 2011

Simplified Logical Model

The Oracle BI server presents as a logically modeleddatabase enabling the Common Enterprise Information

Model.

This provides powerful calculation, computation andfederation capabilities to 3rd party tools as well as our

own.

Oracle BI Server


8/27


9/27

August 4, 2011

Oracle BI Server

Simplified business model view andSimplified business model view and

Open Intelligent InterfaceOpen Intelligent Interface

Business calculation & analytic engineBusiness calculation & analytic engine

Without managed data storeWithout managed data store

Revolutionary request generationRevolutionary request generation

and optimized data source accessand optimized data source access

Insight from largest data warehousesInsight from largest data warehousesand across data sources, systemsand across data sources, systems

Analytical, Operational, Transaction, ExternalAnalytical, Operational, Transaction, External

Relational, MDX, Host, XML, OtherRelational, MDX, Host, XML, Other

Rapid implementation/customization and extensible architectureRapid implementation/customization and extensible architecture

Market-leading scalability, availability,Market-leading scalability, availability,

reliability, performance and TCOreliability, performance and TCO

Simplified business model view andSimplified business model view and

Open Intelligent InterfaceOpen Intelligent Interface

Business calculation & analytic engineBusiness calculation & analytic engine

Without managed data storeWithout managed data store

Revolutionary request generationRevolutionary request generation

and optimized data source accessand optimized data source access

Insight from largest data warehousesInsight from largest data warehousesand across data sources, systemsand across data sources, systems

Analytical, Operational, Transaction, ExternalAnalytical, Operational, Transaction, External

Relational, MDX, Host, XML, OtherRelational, MDX, Host, XML, Other

Rapid implementation/customization and extensible architectureRapid implementation/customization and extensible architecture

Market-leading scalability, availability,Market-leading scalability, availability,

reliability, performance and TCOreliability, performance and TCO

Siebel Analytics Server

Multi-source tuning and load balancing

Parallel Execution Engine

Intelligent multi-level Caching

High performance Siebel Server execution

Scheduling Services (Batch and/or Event-Driven)

Seamless aggregate and fragment navigation

Oracle BI ServerOracle BI Server

Common Enterprise Information ModelMetadata Services

Multidimensional Calculation EngineAggregation and Integration Services

Intelligent Request Generation andOptimized Data Access Services

Clustering Services

Parallel Query Execution Engine

Intelligent Multi-Level Caching Services


Data Mining Services

Clustering Services






10/27

August 4, 2011









Common Enterprise Information Model

Metadata Services



Clustering Services





Clustering Services





Common Metadata

Physical to logical business model

Roadmap to data

Historical data

Real-time data

Inventory data

Oracle BI Server


11/27

August 4, 2011










Metadata Services



Clustering Services





Clustering Services





Calc & Integration Engine

Function ship to appropriate data

sources/Compensation

Optimized performance

SQL < SQL + Oracle BI Server

Time Series, Level based Measures

Oracle BI Server


12/27

August 4, 2011

DM/DW

ODS

Inv.System










Metadata Services



Clustering Services





Clustering Services





Intelligent Request

Generation

Optimized SQL

generation

e.g., Show me salesthrough today for my

highest value customer.

Assure sufficient

inventory.

Historical sales

Todays sales

Rel. to available

inventory

Oracle BI Server


13/27

August 4, 2011

Sample Request Processing

1. User views a dashboard or submits an Answers request

2. The OBI Presentation Server makes a request to the OBI Server to retrieve the

requested data

3. The OBI Server using the .rpd file, optimizes functions to request the data from the

data sources

4. The OBI Server receives the data from the data sources and processes as necessary

5. The OBI Server passes the data to the OBI Presentation Server

6. The OBI Presentation Server formats the data and sends it to the client

Clients

OBI

Presentation

Server

OBI Server Data Sources

1 2 3

456


14/27

August 4, 2011

A Day in the Life of a Query


15/27

August 4, 2011


A logical request comes in asking for

Brand, Closed Revenue (GL)

Service Requests (Call Center) Share of Revenue (Derivation)


16/27

August 4, 2011


Oracle BI Server Cache

The Server will check to see if this request

can be fulfilled via a prior request using

Server Cache.

This is an on-demand intelligent shareable

and secure cache that can support:

Subsets, Aggregations and Derivations


17/27

August 4, 2011


Navigator

If it is the request is cannot be fulfilled by

cache then the server will intelligently

process the request


18/27

August 4, 2011


Multi-Pass/Sub-Request Logic

Does this analysis require sophisticated

analysis such as an OLAP calculation?

[Revenue Share]

The Server will determine the best

possible way to provide this

calculation/computation


19/27

August 4, 2011


Fragmentation Optimization

Does this request span across partitions

or silos of data?

[Closed Revenue and Service Requests]

The server will determine based on the

request if it should navigate to both or only

one. It will automatically resolve fan traps.


20/27

August 4, 2011


Aggregate Navigator

Is there an aggregate that can better

satisfy this request versus hitting the

detail?

{Brand Summary Table}

The Server will apply approprate summary

redirection to provide the quickest

response.


21/27

August 4, 2011


Optimized Query Rewrites

What can be function-shipped down to the

database versus performed

/supplemented by the computation

capabilities of the Server.

The server will provide a consistent set of

functionality to the user regardless of

underlying datasource.


22/27

August 4, 2011


Cache Services

The request once executed will now be

available to other users as a cache entry.


23/27

August 4, 2011

Oracle BI Server

System Services

System Services

Clustering:

Add stacks as needed in a share nothing

clustered environment.

Session Management and Governance:

Query throttling via connection pools and

authorization

Security Services:

Integration with OID, LDAP withsophisticated data driven personalization

mechanisms.


24/27

August 4, 2011

Web

Web

Serve

r

Serve

r

High Availability Deployment

LoadLoadBalancerBalancer

OracleOracleAnalytics WebAnalytics WebW

eb

Web

Server

Server

AdministrationAdministrationToolToolLDAPLDAP

ServerServer

SingleSign-onServer

Oracle BIOracle BIServerServer

Oracle BIOracle BI

ServerServer

ApplicationApplication

DWDW

OracleOracle

Analytics WebAnalytics Web

WebWebCatalogCatalog

WebWeb

CatalogCatalog

MasterMaster

RepositoryRepository

ReplicatedReplicated

RepositoryRepository

SchedulerScheduler

DatabaseDatabase

ClusterClusterControllerController

OAW ReplicationOAW ReplicationAgentAgent

UsersUsers

Stack 2

Stack 1Scheduler ProcessScheduler Process

OtherOtherMart/DWMart/DW


25/27

August 4, 2011

OBIEE Clustering

OBIEE Clustering Components

Cluster Controller Primary Cluster Controller

Secondary Cluster Controller

Clustered BI Servers

Master BI Server

BI Scheduler

Cluster Manager

Failover Mechanisms

Cluster Aware Cache


26/27

August 4, 2011

Webcat Replication

Scenario:

Instance 1 Master Instance Sharing Application

Instance 2, Instance 3 Secondary Clustered Instances exposed to Users

Sawrepaj setup for the replication on both Windows and Unix environments for

performing replication as below

/shared: Instance1 to Instance2

/shared: Instance1 to Instance3

/users: Instance2 to Instance3

/users: Instance3 to Instance2

Edit instanceconfig.xml to enable Replication

Maintain Log Files of Replication


27/27

August 4, 2011

THANK YOUTHANK YOU

Documents

OBIEE - E2 - Architecture