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OBIEE Architecture
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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
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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/8/7/2019 OBIEE - E2 - Architecture
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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
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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
Scheduling Services (Batch and/or Event-Driven)
Data Mining Services
Clustering Services
Parallel Query Execution Engine
Intelligent Multi-Level Caching Services
Scheduling Services (Batch and/or Event-Driven)
Data Mining Services
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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 Model
Metadata 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
Scheduling Services (Batch and/or Event-Driven)
Data Mining Services
Clustering Services
Parallel Query Execution Engine
Intelligent Multi-Level Caching Services
Scheduling Services (Batch and/or Event-Driven)
Data Mining Services
Common Metadata
Physical to logical business model
Roadmap to data
Historical data
Real-time data
Inventory data
Oracle BI Server
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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 Model
Metadata 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
Scheduling Services (Batch and/or Event-Driven)
Data Mining Services
Clustering Services
Parallel Query Execution Engine
Intelligent Multi-Level Caching Services
Scheduling Services (Batch and/or Event-Driven)
Data Mining 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
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DM/DW
ODS
Inv.System
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 Model
Metadata 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
Scheduling Services (Batch and/or Event-Driven)
Data Mining Services
Clustering Services
Parallel Query Execution Engine
Intelligent Multi-Level Caching Services
Scheduling Services (Batch and/or Event-Driven)
Data Mining 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
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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
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A Day in the Life of a Query
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A Day in the Life of a Query
A logical request comes in asking for
Brand, Closed Revenue (GL)
Service Requests (Call Center) Share of Revenue (Derivation)
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A Day in the Life of a Query
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
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A Day in the Life of a Query
Navigator
If it is the request is cannot be fulfilled by
cache then the server will intelligently
process the request
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A Day in the Life of a Query
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
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A Day in the Life of a Query
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.
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A Day in the Life of a Query
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.
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A Day in the Life of a Query
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.
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A Day in the Life of a Query
Cache Services
The request once executed will now be
available to other users as a cache entry.
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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.
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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
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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
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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
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THANK YOUTHANK YOU