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Data Warehousing Portfolio Update

Data Warehousing Portfolio Update. June 11 th 2008 Infobahn - Information Management Event 2008 Grand Hotel Sofia. Paul Gittins, Data Warehouse Sales, NEIOT: Germany & CEMAAS  +44 7802 233328  paul_gittins@uk.ibm.com. Managing Information as a Strategic Asset.

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Data Warehousing Portfolio Update

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  1. Data Warehousing Portfolio Update June 11th 2008 Infobahn - Information Management Event 2008 Grand Hotel Sofia Paul Gittins, Data Warehouse Sales, NEIOT: Germany & CEMAAS  +44 7802 233328  paul_gittins@uk.ibm.com

  2. Managing Information as a Strategic Asset • Information volumes are growing at the rate of 30% per annum • Managing this growth has its challenges • Ever-increasing demand to analyse more information • Ever-increasing demand to manage more types of information • Growing number of users who need access to information • Retaining data for compliance requirements • Total cost of ownership • Key Question: Do you have a strategy for managing this growth ? • IBM InfoSphere Warehouse is the answer

  3. Information On DemandEnd-to-End Capabilities Workforce Optimization Financial Risk Insight Dynamic Supply Chain IBM Offerings Customer & Product Profitability Multi-Channel Marketing Business Optimization Optimization Industry Models, Blueprints & Frameworks IBM Cognos TM1 IBM Cognos 8 Planning IBM Cognos 8 BI IBM InfoSphere Warehouse IBM InfoSphere MDM Server IBM Information Server Flexible Architecture for Leveraging Existing Investments DB2, IMS, Informix IBM Content Manager, IBM FileNet Automation Other Information & Application Sources

  4. Topics • Introduction • Example: NYPD (New York Police Department) • Portfolio overview • Data Warehouse Appliance: Infosphere Balanced Warehouse • Infosphere Data Warehouse • Information Server • Cognos • Data Warehouse Industry Data Models

  5. Marketplace • Data Warehouse (DW) and Business Intelligence (BI) continues to be a major growth area • Priority spend for many clients • New clients seek to deliver reporting but facing constraints from their operational systems • Performance/capacity • Inflexible operational schema • Focus on improved “time to market” • Emergence of appliance-based offerings • Desire to simplify existing DW infrastructure • Data mart proliferation versus Enterprise Data Warehouse (EDW) • Increasing willingness to review existing DW platform assets • Role of application-specific Data Warehouses • Example: SAP Business Information Warehouse (BW)

  6. Applications Query Tools Data Mining / Statistics Federation Data Mart Data Mart Data Mart Data - Information Extract, Transform, Load (ETL) Data Model Data Warehouse Extract, Transform, Load (ETL) Source Source Source Source Source Introduction to Business Intelligence and Data Warehousing Business Users Business Peformance Management OLAP Star Schema Flexible Analysis History Detail Normalised informational operational Optimised

  7. Example: NY Police (NYPD) Crime Information Warehouse (CIW) • Challenge • Lots of data providing historical access only • Difficult to access, disparate systems: Oracle & SQL Server • Absence of integrated view • Use of legacy tools • Solution • Integrated Data Warehouse • Improved delivery of data using • Dashboard • Drill-down • Geo-spatial • Benefits • Move use of data from “reactive” to “pro-active” • Wider use of data • Improved performance of NYPD organisation • Technology: IBM DB2; Cognos; Crime Data Model; Information Server; IBM GBS Consultancy and Server

  8. CIW User Interface http://ciwdemo.dfw.ibm.com/cognos8/

  9. NYPD Crime Information Warehouse (CIW) in action A source for this video : http://www.youtube.com/watch?v=qy7MCu-FhKk

  10. Information On Demand • Optimize Each Transaction • Call Centers, Field Ops OLAP & Data Mining • Merchandising, Inventory, Operations Query & Reporting • Financials, Sales Leveraging Information to Create Business ValueInsightful, relevant information: when and where it is needed Help Solve Crimes by Delivering Suspect List to Detectives Arriving at the Crime Scene 3rd Generation 2nd Generation Optimizing Police Force Deployments Crime Rate Reports 1st Generation

  11. The InfoSphere Balanced Warehouse Real time, ready to go data warehousing solutions The IBM Balanced Warehouse is the completedata warehousing solution comprised of pre-tested, scalable and fully-integrated system components of InfoSphere Warehouse, Server and Storage. • IBM Balanced Warehouses include everything required to serve as a foundation for your business intelligence solutions. Some of the included highlights are: • Robust InfoSphere Warehouse software • The latest in IBM Server technology • High performance IBM storage • Comprehensive total solution support Balanced Warehouse

  12. Business Requirements Warehouse Operations Business Futures Warehouse Function Warehouse Platform InfoSphere Balanced WarehouseA fast track to warehousing IBM modules Preconfigured, pretested allocation of software, storage and hardware to support a specified combination of function and scale Simple Flexible Optimized

  13. InfoSphere Balanced WarehouseBetter than an appliance • Simplicity • Predefined configurations for reduced complexity • One number to contact for complete solution support Balanced Warehouse • Flexibility for growth • Add modules to address increasing demands • Multiple on-ramps for different needs • Reliable, nonproprietary hardware for reusability • Optimized performance • Preconfigured and certified for guaranteed performance • Based on best practices for reduced risk

  14. E7100 for large scale and complex workloads D5100 for high availability D5000 for price-performance C4000 – IBM/BP - up to 4TB C3000 – BP - up to 1.5TB C1000 - BP - up to 350GB C1000 C3000 C4000 IBM Balanced Warehouse – Solution Classes The IBM Balanced Warehouse provides 3 different solution classes that each target and serve a distinct warehousing market segment Workload complexity E-Class Modular for flexible Scale out D-Class Modular for flexible Scale out C-Class Business Partner / IBM 1 3 10 30 100 Terabytes of User data

  15. Balanced Warehouse Offerings Note: Infosphere Data Warehouse software also available separately Application Solutions Growth Solutions Enterprise Solutions D-Class E-Class C-Class Class Name Easy to Deploy Warehousing Applications and Reporting Tools with a Fixed Raw Data Limit Advanced Departmental Data Marts and Growing Data Warehouses Highly Scalable Enterprise Data Warehouses ~$15 to $250K USD $220K to $280K USD (min config) $890K to over $1.8M USD (min config) Scalability Fixed Raw Data Limit High – BCU and Module Very High – BCU and Module Size 50GB to ~5TB 1TB and up 1-2TB and up Users Up to 250 Users No Hard Limits Delivery Primarily Partners (except C4000) IBM Direct Sales and partners

  16. What is the Value of an IBM Balanced Warehouse ?A ‘Ready-to-Go’ Warehouse that is Simple, Flexible and Optimized Simple: • Reduced Complexity: Ships configured and ‘Ready to go’ • Pre-tested: Validated by IBM • Full integration: High Performance DB2 Warehouse delivered ‘load ready’ • Predictable, modular growth through the usage of BCU1 • One number: Single point of contact for all support issues2 Flexible • Modular scalability: Grows with your demands, not your vendor’s • Open and Reusable: Ensures that you are not locked in to proprietary limitations • Spectrum of offerings: Multiple on-ramps to warehousing • Ability to plan for and price the growth of your company’s warehousing needs Optimized: • IBM Balanced Warehouse solutions are thoroughly tested and tuned for performance • Solutions developed through IBM Best Practices of successful client implementations • Low Risk: Guaranteed performance 1 C-Class offerings do not scale through the addition of BCUs due to their specialized form factor, targeting smaller installations. 2 C-Class offerings are supported through associated reseller/distributor service agreements

  17. “No Copy Analytics” Bridging the Operational Insight Divide • The No Copy approach to delivering business analytics has many benefits • Enabling real-time Analytics • Increasing Flexibility • Reducing the Development and Management Effort • Flexibility to add and change Analytical Applications cost effectively • This Approach has had Outstanding Business Results • Improved Customer Service • Fraud Detection • Customer Churn Prediction • Event Based Decision Support • Overall Greater Return On Investment • and Lower Cost of Ownership !

  18. AIX Infosphere Data Warehouse A complete, integrated platform HP/UX Linux/x86 Solaris Windows/x86 Portals & Web Apps Reporting Solutions MS Office / Share-point Universal Access MDX SQL/MDX Web Services Analytical Acceleration No Copy Analytics Advanced Design & Management Extreme Performance Workload Management Design Studio Text Analytics Advanced Capability Data Mining Embedded Data Movement Data Compression On-line Analytical Processing (OLAP) Data Retention Remote Data Access MPP Data Server C-Class D-Class E-Class Linux/ Windows AIX/SUN/HP Platform

  19. Components Standard Eclipse-based GUI

  20. SQL Warehousing (SQW) Infosphere Warehouse Integration with IBM Information Server • Integrated data modeling and SQL tooling in DWE Design Studio complements ETL tool for complete warehouse building • Integrated RDA-based physical data modeling • SQL Warehousing Tool with Eclipse-based data flow and control flow design, web-based administration • Deep DB2 exploitation (e.g. support MERGE syntax) • Websphere App Server-controlled runtime • Special integration with IIS when deployed together • Manipulation within the RDBMS • Especially relevant for maintaining derived structures & data marts

  21. OLAP • New OLAP acceleration • Multiple approaches • MQTs & Query re-write • Cube Views • Cubing Services • Delivers mainstream MDX Function / Robust Data Cubes and support for MDX client tools. • Integrates Alphablox cubing technology, DB2 Cube Views and DB2 optimization technology • Provides native MDX interface • Addresses 75% of OLAP applications • Exception is specialised forecasting and writeback • 2Q08 support for Excel • Benefits • Improve Time-to-Value, Ease of Use / Deployment, lower TCO New

  22. Inline Analytics • Toolbox of pre-built components for analytic functionality (blox) • Scaleable, J2EE-based uses Websphere, Weblogic or Tomcat web-app servers • Rapid application development platform • Enables creation of customised analytical components, embedded into existing business processes and web applications • DWE now ships connectors for non-DB2 RDBMS sources • Complementary to Cognos capabilities

  23. Data Mining & Visualisation • Supports Traditional and Embedded Mining • Scoring, Modelling and Visualisation components using DWE workbench • Algorithms include Segmentation; Classification Tree, Regression and Association Newer • Traditional • Predictive, Statistical Base, API interface • PMML standard interface available • Partners • Embedded • Discovery: patterns • Easier • SQL based calls • Exploiters

  24. Unstructured Analytics • Rich analysis interface for combining structured and unstructured data • Combines search, text analytics and data visualization

  25. Transparent access to non-DB2 dataInformation Integrator (II) Connectors component of IIS included in Infosphere Warehouse (Enterprise Edition) • Potential Uses • Ad-hoc access • Propagation • Prototyping • Productivity • Not a virtual data warehouse • Superior to brute-strength tool-based approach • Examples • Taikang Life (China Insurer) • UK Bank Advanced SQL Advanced SQL Recursive SQL Write Recursive SQL Read User Defined Func . User Defined Func . Common Table Exp. Common Table Exp. Informix IDS

  26. IBM Information Server Delivering information you can trust • Industry leading data-integration platform • Scaleable • Platform/vendor-neutral • Synergy with Infosphere Warehouse • Can exploit new blade technologies

  27. Cognos 8 Business Intelligence Suite • All capabilities against any combination of data sources (OLAP or relational); removes barriers to usage • Hides complexity from users and ensures consistency, integrity and accuracy of information • Business Performance Management (BPM) • Industry Solutions • Cognos 8 Starter Edition ships with Infosphere Warehouse

  28. IBM Industry Data Models • Industry-proven models, including KPIs and compliance metrics • Trusted, single analytical view of the business • Proven data model methodology • Accelerated, business-centric development • Models automatically populate and generate metadata in IBM Information Server • Reduces project complexity and risk • Models: Data Warehouse, Process • Industries • Banking • Financial Markets • Insurance • Telecommunications • Retail • Healthcare • Crime • Airlines Example: Banking DW Model, Business Solution Templates (BSTs) 500+ clients

  29. Summary • IBM offers a best-of-breed portfolio for you to deliver a cost-effective reporting platform • We have all the components necessary • Valid even for clients who have a heritage with other RDBMS eg. Oracle • Strong delivery capabilities (not covered in this presentation) • Consider the benefits of using an appliance-based solution • Focus on solution delivery not individual components • Minimal additional effort to manage an IBM data warehouse • Consultancy effort typically the major element in data warehouse delivery • Assess suitability of existing data schema and relevance of off-the-shelf data model • Understand business reporting requirements • Questions .. ?

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