Oracle Data Integration An Overview with Emphasis in DW Appliances

2. Oracle Data Integration An Overview with Emphasis in DW Appliances

3. Data Integration Where Does Data Integration Fit?Essential Ingredient for Information Agility Business Intelligence • Data Services • Information services • Process Integration • Event driven data integration • Governance and Impact Analysis • Data Integration for BI applications • Event driven BI • Heterogeneous Data Access • Information-based analytics • Report to Source Data Lineage SOA Enterprise DataWarehousing Master Data Management • Extract, Transform, Load • Data Migration, Bulk Data • Data Quality, Profiling

4. Oracle Data WarehouseBreaks Data Bandwidth Bottlenecks • More Pipes • Modular storage “cell” building blocks organized into Massively Parallel Grid • Bandwidth scales with capacity • Bigger Pipes • InfiniBand interconnect transfers data 5x faster than Fibre Channel • Ships Less Data Through Pipes • Query processing is moved into storage to dramatically reduce data sent to servers while offloading server CPUs • Runs the Oracle Database • Database and options run unchanged Exadata Moves a Lot Less Data a Lot Faster

5. EBS Financial Analytical Install Base Site Product Employee Customer Supplier SAP Oracle / Hyperion Data Relationship Management Custom Apps External Apps Oracle Master Data ManagementComprehensive MDM Application Solutions Data Governance Operational Systems Analytical Systems Analytical MDM Apps Operational MDM Apps Dashboards Siebel DW BI &Datamarts PeopleSoft Planning JDE Enterprise schema & Common services Financial Consolidation Budgeting Application Integration Architecture Oracle Fusion Middleware

6. Use Cases for Oracle Data IntegrationUnified Data Integration Platform for Enterprise Projects

7. Introducing ODI-EE

8. Key Data Integration Products • Comprehensive Integration • ELT/ETL for Bulk Data • Data Delivery Services • Process Orchestration • Service Bus • Human Workflow • Data Federation • Replication & Migration • Data Governance • Data Grid New • ELT/ETL for any DB • Changed Data Capture • Native SQL Code Gen • Declarative Design • ELT for Oracle DB • Database Modeling • PL/SQL Code Gen • Flow-based Design • Business Data / Metadata • Statistical Analysis • Time Series Reporting • Integrated Data Quality • Cleansing & Parsing • De-duplication • High Performance • Integrated w/ODI

9. Oracle Core FeaturesComprehensive Data Integration Platform • E-LT Data Processing • Set-based Transformation • Configurable Deployment (E-LT, E-T-L, or others) • Native Code Generation • Declarative Integration Designer • Reverse Engineering of Sources • Intuitive Data Mapping • Built-in Reporting • Metadata Lineage • Graphical Impact Analysis • Native SOA Interoperability • SOA Sources, Targets, or Invoke-able E-LT Jobs, SOA Workflow, etc. • Automatic Error Handling with Data Recycling • Changed Data Capture • Built-in Support for Realtime Data Capture and Streaming • Log-based or Trigger-based • Inline Data Quality • Extensible Knowledge Module Framework

10. Data Integration Core Use CaseComprehensive, Lightweight Data Integration • Key Architecture Benefits: 100% Java, Open APIs, very fast E-LT • Embeddable Java Agent consumes very little CPU or RAM • E-LT Architecture uses DBMS CPUs, not the Application CPUs • Open APIs, Open Metadata, Open XML Knowledge Modules ERPApplication Business Intelligence& Data Warehouse ODI Agent ODI Agent may be deployed in any part of the architecture LKM IKM JKM A D B C$_0 I$ E$ (Errors) LKM C$_1 File C IKM CKM RKM Check-Load Transform Extract-Load

11. Move and transform data. Mixed sources and targets. ODI-EE Value PropositionAgile Data Integration BENEFITS KEY DIFFERENTIATED FEATURES • Performance>>> Heterogeneous “E-LT” • Flexibility >>> Event-Driven Platform • Productivity>>> Declarative Design • Open>>> 100% Java and SOA Native • Hot-Pluggable>>> Knowledge Modules 11

12. Differentiator: E-LT ArchitectureHigh Performance Transform Extract Load • Conventional: Separate ETL Server • Proprietary ETL Engine • Poor Performance • High Costs for Separate Standalone Server • IBM & Informatica’s approach • Oracle: No New Servers • Lower Cost: Leverage Compute Resources & Partition Workload efficiently • Efficient: Exploits Database Optimizer • Fast: Exploits Native Bulk Load & Other Database Interfaces • Scalable: Scales as you add Processors to Source or Target • Benefits • Optimal Performance & Scalability • Better Hardware Leverage • Easier to Manage & Lower Cost Conventional ETL Architecture Next Generation Architecture “E-LT” Transform Transform Extract Load 12

13. Real Time Data Warehouse Differentiator: Changed Data CaptureEvent-Driven Framework for RealtimeData Warehouse Logs Logs Logs Source Systems Data Warehouse Redo Logs / Triggers Change Tables Subscription Views Staging Area Data Warehouse Source DB’s Transactional RDBMS CDC Records CDC Records CDC Records CDC Records CDC Records CDC Records CDC Records CDC Records CDC Records Transactional RDBMS Transactional RDBMS

14. Integrated with Oracle BIEE Plus Support for relational, R-OLAP, OLAP sources & targets Report-to-source lineage Drill-in from a Report Get query, DW schema, source tables, transforms Gain confidence in analytics Unified infrastructure Unified metadata & lineage Integrated Data Quality Unified data access, Common administration & monitoring Integrated scheduling & security Common auditing & tracing Common error handling Focus on Oracle BIEE Suite PlusUnify Data Integration with Business Intelligence Oracle BIEE Suite Plus InteractiveDashboards Ad hocAnalysis ProactiveAlerts MicrosoftOffice Reporting & Publishing Common Enterprise Information Model Oracle Business Intelligence Server Data Flow Design & Drill Enterprise Data Warehouse • Oracle RAC • Teradata • Netezza…etc Oracle Data Integration Suite Data Distribution & Delivery APIs Metadata Lineage Bulk/Trickle Loading Changed DataCapture MasterData Data Quality& Profiling ODI Knowledge Module Framework Bulk and Real-Time Data Processing Oracle EBS Data Warehouse Information Assets CDC SAP/R3 Other Sources PeopleSoft MessageQueues 14

15. Report to Source Data LineageExplore Lineage from Target Columns to Source Columns

16. Pre-Built BI Analytic Applications Pre-built Metrics, 5000+ Dashboards, Data Warehouse 350+ Star Schema Implementation Time: 3-4 Weeks Works with EBS, PSFT, SAP, SEBL, JD-Edwards Sources Biggest Savings: Pre-built ETL Faster & Lower Cost to Build & Maintain ETLs Knowledge Module Architecture Enables Efficient Development of Packaged ETL Reduce Complexity and Size of Code Reuse DW Creation, Update, Load Times Value-add Modules (e.g. SOX) Extensible by Customers & System Integrators Data Flow Oracle Data Integrator ODI Knowledge Modules for BI Analytic Applications Pre-Built ODI Interfaces and Transformation Packages for Analytic Applications Metadata Repository Bulk Transform. Changed Data Capture Data Integrity Data Quality ODI Connectivity Framework Bulk and Real-Time Data Processing Focus on OBI Analytic ApplicationsOverview Oracle BI Analytic Applications Sales Contact Center Order Mgt MKting Supply Chain HR Finance Analytics Data Warehouse Oracle BI Server and Semantic Layer Build from Scratch Pre-built BI Apps Training Metrics & Dashbrds DW Design ETL Mapping 50% Oracle EBS Data Warehouse SAP/R3 CDC Information Assets Other Sources People Soft Message Queues Weeks or months Years or quarters

17. Authentication Data Services Logging Services API Layer Focus on Oracle | Hyperion ApplicationsLeveraging EPM with Embedded Data Integration Oracle Hyperion Planning Oracle Hyperion Financial Mgt Oracle Hyperion Essbase Oracle Hyperion Application Adapters Planning API HFM API Essbase API Oracle | Hyperion Data Access Oracle Data Integration Suite Data Distribution & Delivery APIs Metadata Lineage Bulk/Trickle Loading Changed DataCapture MasterData Data Quality& Profiling ODI Knowledge Module Framework Bulk and Real-Time Data Processing Oracle EBS Data Warehouse Information Assets CDC SAP/R3 Other Sources PeopleSoft MessageQueues

18. Hierarchy management Derivation/inheritance Classification, categorization Attribute management Change management Streamlined, automated Valid-from, Valid-to ranges Compare any 2 versions Business-user driven Easy user declarative tool Specify business rules Multi-user collaboration What-if & historical analysis Meets IT requirements Synchronize with operational systems Complete auditing, fine-grained security Configurable, no coding DRM Import/Export Profiles Oracle Data Integrator ODI Knowledge Modules for DRM Metadata Repository Bulk Transform. Changed Data Capture Data Integrity Data Quality ODI Connectivity Framework Bulk and Real-Time Data Processing Oracle EBS Data Warehouse SAP/R3 CDC Other Sources People Soft Message Queues Focus on Hyperion MDMFoundation for Data Relationship Management (DRM) Hyperion Data Relationship Management Information Assets

19. Operational Analytic Legacy Hyperion Data Relationship Management Analytics Hierarchy Governance SAP Key Performance Siebel CRM Query / Reporting People Soft Enterprise Reporting E-Business Suite Financial Apps JD Edwards Budgeting HR Planning & Forecasting Master Hierarchies and Versions Org Struct Accounts Entities Cost Centers Geography Hyperion Data Relationship ManagementClosed-loop Master Data Management Oracle Data Integrator & Oracle Data Quality Oracle Data Integrator & Oracle Data Quality

20. ODI-EE A Look Ahead

21. ODI for Oracle FusionData Integration as a Key Fusion Differentiator • Fusion Applications • Built-in, Automated Data Replication among ERP Applications • Fusion Business Intelligence • Pre-built Analytics from Fusion ERP Applications • Automatic Mapping and Model Updates (Application-driven) • Fusion Master Data Management • Data Replication, Conflict Detection and Conflict Resolution • Fusion w/Essbase • Fusion Financials (Automatic Financial Consolidation) • Pre-built Essbase Content with Apps and Business Intelligence

22. High-Level Data Integration RoadmapTowards a Unified ETL Platform UnifiedTeam 2009 2011 UnifiedPlatform • OWB/ODI Investments are Fully Protected • No Forced Migrations • Natural Upgrade Path • Unified Platform aims to be a Superset of Existing Products – no regression 2009 2010

23. MBeans Server Registry Any Application Container Web Service Container Servlet Container Any Java App JDeveloper Any Application Any Application Any MBeans App ODI Transform. Service ODI Agent ODI in JDev ODI Data Services ODI Thin Client ODI SDK APIs ODI MBeans for ODI Agent ODI SDK APIs Data Sources Connection Pool Sources and Targets Designer Operator Security Topology Repository Data Sources Sources Data Sources Target Data Sources - - - Repository Data Sources Sources Data Sources Target Data Sources Repository Data Sources Sources Data Sources Target Data Sources --- --- --- --- --- --- --- --- --- --- --- --- Best-of-Breed Applications Legacy ERP PLM CRM --- --- --- --- --- --- ODI J2EE Deployment ArchitectureLogical Architecture Overview Any Web App WLS Any Java App RDBMS – ODI Repositories ODI Work Repository ODI Work Repository ODI Master Repository ODI Work Repository

24. ODI 11gR1 New FeaturesAvailability Planned for 1HCY10 Timeframe JDeveloper-based Tooling J2EE deployment option (using Weblogic Server) Standalone Option is Preserved – using Jetty JPS-based Security (external password management) Enterprise Scheduler (ESS) Integration Enterprise Manager Integration New Thin Client (consolidated + more mgmt features) Set-based Operators and Temporary Index Management Java SDK APIs for Improved Embedability JDE Enterprise One Knowledge Modules (v8.x and higher) SAP ERP Knowledge Modules (v4.6 and ECC 6.0) SAP iDocs Knowledge Modules (v4.6 and ECC 6.0) SAP BW Knowledge Modules (v3.5 and v7.0) 24

25. Customer Examples

26. Enterprise Data WarehouseRaiffeisen Bank Meets legal requirements for data consolidation in the head office (Basel II, Investor reporting) Seamless and realtime Capital Market reporting to investors and stakeholders Single-source of truth for business information – supports Business Intelligence and EDW One standardized enterprise data model over the whole RZB Group Reduction of core integration/development costs through central development practice Reduced time to market for new Group applications through central interface development Performance Issues with existing ETL Tool (IBM DataStage) New functions required for the next DWH releases (realtime, replication, etc) Business Challenges • Costs for Enterprise Data Warehouse infrastructure were growing too fast • EDW processes not keeping up with 24x7 operations, ETL batches too slow IT Challenges Oracle Data Integration Solution Benefits

27. Order Replenishment, Online CatalogJ. Crew Simplified the end-to-end data integration with all their core IT systems and database platforms to reduce the total cost of ownership of their order replenishment and cataloging Benefited from the Oracle advantage in batch processing, bulk data transformation for increased performance Successfully leveraged SAP and Teradata integration to phase out legacy systems and ultimately reduce costs Order replenishment for online catalog system Define new corporate standard for data integration Better integrate data across 175 retail stores and 52 outlet chains Business Challenges IT Challenges • Replace antiquated home-grown solution of scripts • Teradata bulk data support, and help integrate data across SAP, Red Prairie Inventory systems Oracle Data Integration Solution Benefits

28. Financial Services, ReinsuranceNew Reinsurance, Division of the Munich Re Group Seamlessly integrated across (Oracle applications (E-business Suite, Siebel CRM) SAP, IBM, etc) to manage the regeneration of all code, scripts, and metadata across the different environments. Lowered the cost of development by taking advantage of ODI’s declarative model, ease of use, and team collaboration capabilities. NRC benefited from the flexibility and standards based approach of ODI, helped leverage the existing environment. Needed quality of data but uncompromising on the cost to meet that objective. Data interactions between multiple complex systems, including both SAP and homegrown insurance applications Business Challenges IT Challenges • Hard to modify and maintain manually-developed data transfer programs. • Data transfers as part of reinsurance, risk transactions Oracle Data Integration Solution Benefits

29. Improve Inventory ControlRoss Seamless data integration from heterogeneous sources leveraging SOA helped to create a more flexible, standards based integration approach 73% Bulk data transfer performance improvement Together with Oracle SOA Suite (Oracle BPEL PM) provided business optimization, process visibility, exception handling Closed loop processing using BAM and Data Integration combined eliminated ordering/replenishing inventory errors by reducing inaccurate data Hard to consolidate consistent, accurate inventory information across over 800 multiple store chains Lack of visibility to errors to the business Higher cost and time to delivery of new value Business Challenges IT Challenges • Current state was complex, didn’t scale, and difficult to manage • Non-standard approach required coding paradigm, inconsistent error handling Oracle Data Integration Solution Benefits Dain Hansen

30. Shared Data ServicesVerizon ODI + SOA helped to build out a shared services layer which helped provide greater flexibility These shared services consolidate database (DB2, Sybase, Informix to Oracle), consolidate ERP (PeopleSoft HR/Payroll, Decommissioning SAP), consolidate middleware (Oracle FMW) and consolidate BI/ETL In addition the program helped to decommission Cystal and Cognos and adopt Oracle BIEE Streamline and automate business processes around new hire on boarding Provide better business insight and manage FiOS supply chain Business Challenges IT Challenges • Lower the cost of rewriting SAP, PSFT & Legacy interfaces (about 209) through custom code • Lower the cost of IT infrastructure from multiple systems Oracle Data Integration Solution Benefits Dain Hansen

31. Sales and Marketing Data Warehouse Nestle Replaced weekly insertion with daily recording of change in status with time imprint for all clients—allowing for more effective client follow-up, for example Improved response times by transferring reporting processes to the data warehouse Improved reactivity for restocking requirements thanks to daily updates on stock quantity and value for each store Provided overall view of the status of business processes, resulting in improved user communication Hard to consolidate consistent, accurate inventory information across over 800 multiple store chains Lack of visibility to errors to the business Higher cost and time to delivery of new value Business Challenges • Enable the marketing and CRM team to better target its campaigns and activities across 50 countries • Anticipate future reporting challenges, in light of the strong increase in the volume of production data IT Challenges • Manage a data warehouse for operational transactions and marketing information • Scale available for high-value-added actionable data on clients, orders, stock, etc. Oracle Data Integration Solution Benefits Dain Hansen

32. Questions

34. The preceding is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions.The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.