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Criteria for D/W Platform Selection

Criteria for D/W Platform Selection. Simple Architecture Easy to deploy the solution with minimal efforts Scalable (Scale Out - Scale Up) Ability to handle increasing data sizes and workloads with simple additions to the architecture, without requiring a re-architecture Proven and Supported

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Criteria for D/W Platform Selection

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  1. Criteria for D/W Platform Selection Simple Architecture • Easy to deploy the solution with minimal efforts Scalable (Scale Out - Scale Up) • Ability to handle increasing data sizes and workloads with simple additions to the architecture, without requiring a re-architecture Proven and Supported • No risks approach , go for only proven solution options Affordable & Manageable $$$ Savings • Significantly faster project delivery • Low total cost of ownership (TCO) over a multi-year period • Hardware, software, services, required customer support • Minimal support tasks requiring DBA/System Administrator intervention • Provide a single point of control to simplify system administration. Flexible • Easy to add new subject areas, even totally new LOB due o acquisitions • Easy to make changes to meet the dynamic business needs • Comprehensive solution for the spectrum of eventual requirements for data and its access • Proven ability to support multiple applications from different business units, leveraging data that is integrated across business functions and subject areas.

  2. Oracle Facts • Current Solution • Four Vendors: H/W by Sun , S/W by Oracle , Storage by NetApp, Network by Cisco • We drive the coordination and optimization efforts across vendors • We incurs the risk of solution performance • Sub Optimal throughput - 500 Mb/sec vs. industry average of 2G/sec • Does not scale linearly • On RAC queries cannot take advantage of all cluster nodes (H/W Resources) • Shared Disk (SMP) architecture suffers from contention as the platform is scaled out • Requires highly tuned physical design effort • Manually coded Partition management and Query Tuning • Complex ETL processes and aggregation strategy • Higher Storage management (DBA, Storage Engineers) • Successful Oracle Multi-Terabyte Implementations • Large number of small storage arrays • Oracle Automated Storage Management • Hash sub-partitioning • Army of rocket scientists DBAs

  3. Business Impact • Slower speed to market • Complex Architecture • More Data movement • Higher TCO • Higher development cost • Higher Operational and KTLO cost • Site Traffic cannot meet next day SLA • Takes 14+ Hrs just to load into staging after extensive tuning efforts • EDW and Data marts cannot be loaded in next day SLA • Availability of All types Information is not guaranteed • in case of failure - Catch-up takes long time , No window to fix to meet SLA • X% reports on Oracle Platform timed out in Oct’08 • Inability to answer Unknown questions • Limited Ad-hoc functionality

  4. Industry Trend for Multi Terabyte Data Warehouses Trends • MPP Technology and Columnar Databases • DW Appliances • Ease of installation • Faster startup • Guaranteed performance SLAs • Single source of service and support • Lower resources to manage the environment • Lower TCO and Faster ROI Courtesy: Donald Feinberg   - Gartner • Focus on Business Aspect • Let technological achievements and innovations take care of architecture and design complexities Courtesy: Dr. Claudia Imhoff – Well Known BI Veteran Vendors • Born MPP • Teradata, Netezza, Dataupia, ParAccel, Vertica, Greenplum, Aster • Data Allegro now Microsoft • IBM Db2 with BCU • Oracle • Recently announced “Exa Data” a DW appliance to catch-up with trend • Not Proven yet • Market Share for Multi Terabyte DW • Teradata and Netezza holds Major • Oracle Lost # of Customers • Oracle to Teradata ~ 200 counts • Oracle to Netezza ~ 20 counts • Vertical – Online Advertising Segment

  5. Inappropriate Platform Selection - Consequences • Long development cycles • High numbers of support staff required cost expansion • “Throwing hardware at problems” as a solution • Users reverting to old means of data access with user interfaces that are not friendly • A technology-focused culture rather than a user culture in IT • Complex vendor relationships • Hard to incorporate legacy systems and unstructured data • Inability to keep pace with growing data volumes and user demands • Inability to show profitability from data warehouse efforts, leading to slow program demise

  6. Move Towards DW Appliances • Packaged, balanced configurations based on the size of the database. • Simplified and accelerated installation and setup • Ease of maintenance and support through a single source. • Simple, integrated management of the system as a single entity. • Lower number of resources required to manage the system. • Guaranteed performance • Specific implementation costs, such as configuration design and balancing, are embedded in the data warehouse appliance price. • Lower total cost of acquisition (TCA) and/or TCO. Courtesy: Donald Feinberg   - Gartner - Data Warehouse Appliances Are More Than Just Plug-And-Play

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