Insert Picture Here Oracle Data Integration An Overview

Oracle Data Integration An Overview with Emphasis in DW Appliances

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

Oracle Data Warehouse Breaks Data Bandwidth Bottlenecks • More Pipes • Modular storage “cell” building blocks organized into Massively Parallel Grid • Bandwidth scales with capacity • Bigger Pipes • Infini. Band interconnect transfers data 5 x 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

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

Use Cases for Oracle Data Integration Unified Data Integration Platform for Enterprise Projects Data Integration BI & Data Warehouse • • • Real-time Data Warehouse for BI • Populate Warehouse with High Performance ODI • Aggregates and aligns data for operational analytics, performance management, etc Bulk-load historical data to new application Synchronize new and old applications Complex transformations, CDC Ensure database-level consistency across applications bidirectional Modernization Data Migrations & Consolidation • Mainframe / i. Series sources to Oracle RAC • Re-architect legacy batch processing to SOA and ODI-EE • Unification of structured and unstructured data • Upgrade Applications or Migrate to New Schema • Single-time Bulk load and/or keep in Sync with ongoing translation, delivery of data. • Applications merge support SOA Initiatives Master Data Management • Establish Messaging Architecture for Integration • Incorporate Efficient Bulk Data Processing with ODI • Providing data access, transformation etc. as services within SOA • • Create Single View of the Truth in real time Aggregating multiple operational sources Synchronize Data with ODI-EE Supports master data stores, publishes master data changes to all consumers

Introducing ODI-EE

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

Oracle Core Features Comprehensive 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

Data Integration Core Use Case Comprehensive, 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 ERP Application JKM ODI Agent Business Intelligence & Data Warehouse ODI Agent may be deployed in any part of the architecture LKM IKM A D B C$_0 LKM C$_1 I$ File C E$ (Errors) IKM CKM RKM Extract-Load Transform Check-Load

ODI-EE Value Proposition Agile Data Integration Move and transform data. Mixed sources and targets. BENEFITS 1. 2. 3. 4. 5. Performance Flexibility Productivity Open Hot-Pluggable KEY DIFFERENTIATED FEATURES >>> >>> >>> Heterogeneous “E-LT” Event-Driven Platform Declarative Design 100% Java and SOA Native Knowledge Modules 11

Differentiator: E-LT Architecture High Performance Conventional: Separate ETL Server • • Proprietary ETL Engine Poor Performance High Costs for Separate Standalone Server IBM & Informatica’s approach Conventional ETL Architecture Extract Transform Load 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 Next Generation Architecture “E-LT” Transform Extract Load Transform 12 12

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

Focus on Oracle BIEE Suite Plus Unify Data Integration with Business Intelligence • Oracle BIEE Suite Plus Interactive Dashboards Ad hoc Analysis Proactive Alerts Microsoft Office Reporting & Publishing Integrated with Oracle BIEE Plus • Support for relational, R-OLAP, OLAP sources & targets Common Enterprise Information Model Oracle Business Intelligence Server Design & Drill Enterprise Data Warehouse • • Data Flow Data Distribution & Delivery APIs Bulk/Trickle Loading Changed Data Capture Master Data Quality & Profiling ODI Knowledge Module Framework Bulk and Real-Time Data Processing Information Assets Other Sources Oracle EBS CDC SAP/R 3 People. Soft Unified infrastructure • Oracle RAC • Teradata • Netezza…etc Oracle Data Integration Suite Metadata Lineage Report-to-source lineage • Drill-in from a Report • Get query, DW schema, source tables, transforms • Gain confidence in analytics • • Unified metadata & lineage Integrated Data Quality Unified data access, Common administration & monitoring • Integrated scheduling & security • Common auditing & tracing • Common error handling Data Message. Warehouse Queues 14

Report to Source Data Lineage Explore Lineage from Target Columns to Source Columns

Focus on OBI Analytic Applications Overview • Oracle BI Analytic Applications Sales Contact Center Order Mgt Analytics Data Warehouse Supply Chain MKting HR Finance • • • Metadata Repository Pre-Built ODI Interfaces and Transformation Packages for Analytic Applications Bulk Transform. Changed Data Capture Data Integrity Data Quality • Pre-built Metrics, 5000+ Dashboards, Data Warehouse 350+ Star Schema Implementation Time: 3 -4 Weeks Works with EBS, PSFT, SAP, SEBL, JDEdwards Sources Biggest Savings: Pre-built ETL Faster & Lower Cost to Build & Maintain ETLs • Oracle Data Integrator ODI Knowledge Modules for BI Analytic Applications • • • Oracle BI Server and Semantic Layer Data Flow Pre-Built BI Analytic Applications 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 Build from Scratch Pre-built BI Apps Training Metrics & Dashbrds ODI Connectivity Framework DW Design Bulk and Real-Time Data Processing Informatio n Assets Other Sources Oracle EBS CDC People Soft SAP/R 3 M es sa ge Q ue ue s 50% Data Warehouse ETL Mapping Years or quarters Weeks or months

Focus on Oracle | Hyperion Applications Leveraging EPM with Embedded Data Integration Oracle Hyperion Planning Oracle Hyperion Financial Mgt Planning API Oracle Hyperion Essbase HFM API Oracle Hyperion Application Adapters Hyperion Planning Essbase API Metadata Discovery & Model Creation Oracle | Hyperion Data Access Authentication Data Services Hyperion Financial Management Hyperion Essbase ü ü ü API Layer Use Essbase KM ü ü Extracts Dimension Members Logging Services Extract Data Use Essbase KM ü ü Loads Data Distribution & Delivery APIs Metadata Lineage Bulk/Trickle Loading Changed Data Capture Master Data Bulk and Real-Time Data Processing Other Sources Oracle EBS CDC SAP/R 3 People. Soft ü ü Cube Refresh Consolidate Calculate Other Features Data Quality & Profiling ODI Knowledge Module Framework Information Assets ü Loads Dimension Members Oracle Data Integration Suite ü Data Message. Warehouse Queues

Focus on Hyperion MDM Foundation for Data Relationship Management (DRM) • Hyperion Data Relationship Management • Derivation/inheritance • Classification, categorization • Attribute management DRM Import/Export Profiles • • ODI Knowledge Modules for DRM Bulk Transform. Changed Data Capture Data Integrity Bulk and Real-Time Data Processing Other Sources Oracle EBS CDC SAP/R 3 People Soft M es sa ge Q ue ue s Data Warehouse Business-user driven • • Data Quality ODI Connectivity Framework Information Assets Change management • Streamlined, automated • Valid-from, Valid-to ranges • Compare any 2 versions Oracle Data Integrator Metadata Repository Hierarchy management • 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 18

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

ODI-EE A Look Ahead

ODI for Oracle Fusion Data 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

High-Level Data Integration Roadmap Towards a Unified ETL Platform Unified Team OWB 10 g. R 1 OWB 10 g. R 2 2009 2011 OWB 11 g. R 2 Unified Platform ODI 10 g. R 3 ODI 11 g. R 2 ODI 11 g. R 1 2009 2010 • OWB/ODI Investments are Fully Protected • No Forced Migrations • Natural Upgrade Path • Unified Platform aims to be a Superset of Existing Products – no regression

ODI J 2 EE Deployment Architecture Logical Architecture Overview Any Web App Any Java App JDeveloper Any Java App WLS ODI in JDev Any Application Designer Any Application Container Web Service Container Any MBeans App Any Application ODI Transform. Service ODI Thin Client Topology MBeans Server Registry ODI Agent Operator Security ODI SDK APIs Servlet Container ODI MBeans for ODI Agent ODI SDK APIs ODI Data Services Data Sources Connection Pool RDBMS – ODI Repositories ODI Master Repository Data Sources Data Sources Repository Data Sources ODI Work ODI Repository Work ODI Work Repository Target Data Sources and Targets -------- --- Legacy ERP PLM -------CRM -------Best-of-Breed Applications

ODI 11 g. R 1 New Features Availability Planned for 1 HCY 10 Timeframe • • • • JDeveloper-based Tooling J 2 EE 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 (v 8. x and higher) SAP ERP Knowledge Modules (v 4. 6 and ECC 6. 0) SAP i. Docs Knowledge Modules (v 4. 6 and ECC 6. 0) SAP BW Knowledge Modules (v 3. 5 and v 7. 0) 24

Customer Examples

Enterprise Data Warehouse Raiffeisen Bank Business Challenges • • Costs for Enterprise Data Warehouse infrastructure were growing too fast EDW processes not keeping up with 24 x 7 operations, ETL batches too slow IT Challenges • • Performance Issues with existing ETL Tool (IBM Data. Stage) New functions required for the next DWH releases (realtime, replication, etc) Oracle Data Integration Solution Benefits • 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

Order Replenishment, Online Catalog J. Crew Business Challenges • • • Order replenishment for online catalog system Define new corporate standard for data integration Better integrate data across 175 retail stores and 52 outlet chains 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 • • • 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

Financial Services, Reinsurance New Reinsurance, Division of the Munich Re Group Business Challenges • • 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 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 • • • 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.

Improve Inventory Control Ross Business Challenges • 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 • • 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 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

Shared Data Services Verizon Business Challenges • Streamline and automate business processes around new hire on boarding Provide better business insight and manage Fi. OS supply chain • 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 ODI + SOA helped to build out a shared services layer which helped provide greater flexibility These shared services consolidate database (DB 2, Sybase, Informix to Oracle), consolidate ERP (People. Soft 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

Sales and Marketing Data Warehouse Nestle Business Challenges • • Enable the marketing and CRM accuratebetter target Hard to consolidate consistent, team to inventory information across over 800 multiple store chains its campaigns and activities across 50 countries • • Anticipate future to errors to the business light of the Lack of visibility reporting challenges, in • strong increase in theto delivery of new value Higher cost and time 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 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

Questions

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