Data Virtualization an Overview

1. Data Virtualization an Overview Ian Pestell Director EMEA Operations

2. Is Your Data an Asset or a Liability? “Managers spend two hours a day looking for information they need, and almost half the data is useless once they get it” Source: Accenture

3. Application Data Legacy Data Data within SOA • SOA Architectures implement Business Process • Through Application Logic • Operating on Data • Data from many sources • Existing Legacy systems • Databases, Web Services, Files • Complicated by package applications, ERP and CRM • Data Services are often addressed late in SOA SOA Business Process Business Process Application Logic Application Logic Data

4. Business Solutions Dashboards Reporting SOA Code within the Application? File Extracts / Database Replications? ETL / Physical Warehouses, Marts, Stores? EII / Virtual? Flat Files Packaged Apps RDBMS Data Warehouses Web Services Data Integration Options Constant Change Data Integration Challenge Existing Data Siloed & Complex

5. Data Consolidation / ETL Application • Physical data movement via scripts • Data is extracted from source systems • Transformed • Data Cleansing, OLTP to OLAP • Loaded into target system • Physical Data Warehouse, Mart, Operational Data Store • Very large volumes of data • High degree of transformation • Data is only as current as last load MDM Hub Data Mart / ODS Data Warehouse ETL Server Files Databases Applications

6. Data Federation / EII • Virtual data views via modelling • Data is left in-situ within data sources • EII server federates and transforms data on demand • No Data Warehouse required • High degree of flexibility in adding new data sources • Lower development & operating costs • Moderate to high data volumes • Low to medium transformations • Data is ‘near’ real-time Application EII Server cache Files Databases Applications

7. Application Data Legacy Data Solutions to Data Integration – Application Integration • Integration performed in the application logic • Data sources require WS API • Vendor – bespoke • Access to WS API via ESB • Supported by standards • ws-orchestration, ws-choreography • Disadvantages • Complex logic with Application • High develop time • Maintenance of change • Enabling WS APIs for data • High load on ESB • Latency of ESB Application Logic Enterprise Service Bus WS API WS API WS API WS API

8. Application Data Legacy Data Solutions to Data Integration – Data Services Layer • Implement Data Services Layer • Provides set of reusable data services • WS access into ESB • Connects to data sources using native interfaces • Integration / optimization only done within data layer • Reduces load Application Logic Enterprise Service Bus Data Services Layer

9. Business Solutions Dashboards Reporting Applications Positions POs Orders Trades Vendors Invoices Customers GLs Employees Flat Files Packaged Apps RDBMS Data Warehouses Web Services You Can Integrate Data Differently Real-time Information Virtualizes Virtual Data Layer Abstracts Federates Existing Data Siloed & Complex

10. Business Applications Dashboards Reporting SOA Flat Files Packaged Apps RDBMS XML Docs Data Warehouses Composite’s Mission • Composite helps IT teams who need to build new applications faster, • by providing data services middleware that lets them access any data in the enterprise… and deliver it on demand. Existing Data

11. Data Engine For Operational BI Data Services (SOA) NA Sales What We Do Information Infrastructure Operational Reporting Access Combine • Single Source for all Data • Standardized Access • Reusable Data Services Deliver >>> On Demand <<< • Drug Discovery • Order Management • Portfolio Management • Inventory Management App

12. Composite Software at a Glance • Privately-held, Silicon Valley firm • Strong Business Model & Team • Best-of-Breed Virtual Data Integration / EII • Discover, Virtualize, Abstract & Federate • Proven Business and IT Value • Increased Flexibility • Greater Agility • Lower Costs IE 2008 Editor’s Award Consumer/Retail Energy and Utility Financial Services Life Sciences Technology Financial Services Life Sciences Top 5 Inv Bank Top 5 Comm Bank Top 5 I-Bank Public Sector Top 5 I-Bank Top 5 I-Bank Mutual Fund

13. How we do it – Data Views Composite View Step 1 - Development: Build and Publish a View (A View contains Metadata on the actual data source – format, type, location, access, etc.) Data Source 1 Data Source 2

14. Composite Applications Analytics Reporting How we do it – Data Views Step 3 – Runtime: Deliver Information (Combined data creates meaningful information) Composite View Step 1 - Development: Build and Publish a View (A View contains Metadata on the actual data source – format, type, location, access, etc.) Step 2 – Runtime: Access and Combine (Queries are optimized for speed and efficiency) Data Source 1 Data Source 2

15. Request Results Auto-Generated WSDL Deliver Results Combine Data/ Model Access Data Auto-Generated WSDL Combine Data/ Model Access Data Request Results Deliver Results Composite Lets You Easily Construct Data Services

16. Composite Information Server Architecture Easily Works Within Complex Environments Client and Enterprise Applications S. Web Services (SOAP/JMS) Relational SQL (ODBC/JDBC/ADO.NET) Composite Studio Administration API COMPOSITE INFORMATION SERVER Modeler Security Manager Data Services Pre-Built Customer-Built (Views, SQL Script, XQuery, Java) Composite Web Manager Cache Query Processing Engine Security Relational (SQL) Java APIs WS (SOAP/JMS) MF Adapter RDBMS Excel Web Service Flat File Custom Application Mainframe

17. BI Tools Excel Composite Apps SQL / WS Complex API Enterprise Data Why Composite Application Data Services™ Adaptor Application Views

18. Orchestration ESB / BPM DATA DATA DATA DATA Transaction Services App Server Files Packaged Apps Custom Apps XML/HTTP XML Files SOAP/HTTP Data Services are a Critical SOA Component Composite Applications • Data services stand alone • Transaction services stand alone • Data services integrated with transaction services • Data services with orchestration using a business process management tool or ESB • Data services WSDL stored in a UDDI registry Registry Data Services Info Server Data Services (Info Server) DATA DATA DATA DATA DATA DATA “Over 60% of SOA services will bedata services”Source: IDC

19. NY Investment Bank – New e-business application • Implementation of new e-business application • Initial estimate 2 man years • 1 year application • 1 data integration • Using EAI approach

20. NY Investment Bank – New e-business application • Implementation of new e-business application • Initial estimate 2 man years • 1 year application • 1 data integration • Using EAI approach • Using Composite Data services • Reduces Data integration from 12 Month to 4 Months • Created optimized and re-usable data services • Introduced abstraction layer between application and data

21. DATA DATA DATA Flat Files DATA DATA DATA Packaged Apps RDBMS XML Docs Data Warehouses Data Services At Work - New York Bank Multiple Projects 1. Prime Brokerage Reporting 2. Risk Management 3. Back Office Reconciliation 4. Portfolio Balancing • Data Required (100%) • Reuse (nearly 40%) • Lower Impact (75% or more) • Faster Response (up to 80%) Business and IT Benefits Data Services Layer DATA DATA DATA Existing Data

22. Situation & Requirements: Scandinavian construction materials retailer/wholesaler, 25 stores Business requirement: detect and address variances between planned and actual payroll expense Business user: Office of the CFO Technical requirement: Expose and combine SAP R/3 and in-house budget data Solution: Create views to SAP payroll information Create views to other payroll information Build roll-up view for analysis Expose view into budget system Benefits: More accurate variance information sooner Rapid application development Single View of Payroll and VariancesHusasmidjan, Inc. Composite Information Server Rollup View Local views normalize across different stores and apps Legacy Payroll data sources Files