Big Data & Information Management Channel Manager

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Information Management and Business Analytics, DB2, Netezza, InfoSphere portfolio and Cognos Data Manager.

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Big Data & Information Management Channel Manager

  1. 1. Information Management & Business Analytics April 3rd 2014 Big Data/Information Management Mark Chandler Big Data & Information Management Channel Manager Email: mark.chandler@uk.ibm.com Mobile: 07738 310900
  2. 2. Information Management & Business Analytics April 3rd 2014 Agenda  Where do you go to for information?  Business Analytics & DB2  Netezza & Business Analytics  InfoSphere portfolio & Business Analytics  Cognos Data Manager
  3. 3. Information Management & Business Analytics April 3rd 2014 The Right Tools IM Exclusive BP Portal Business Partner Locator Tool PartnerPlan & SVP Readiness Dashboard Web Content Syndication Ready to Execute Campaigns Software Briefing Center IBM Market Insights (Comp) All labels are hyperlinked on this page in Slide Show mode Financing a Smarter Planet Getting Started with Social Media IBM Global Financing
  4. 4. Information Management & Business Analytics April 3rd 2014 Cognos & DB2
  5. 5. Information Management & Business Analytics April 3rd 2014
  6. 6. © 2013 IBM Corporation© 2013 IBM CorporationApril 9, 2014 Make Better Business Decisions...Faster Accelerate Business Intelligence Performance with Cognos BI 10 & DB2 10.5 <<Speaker Name Here>> <<Speaker Title Here>> <<For questions about this presentation contact Speaker Name speaker@us.ibm.com>
  7. 7. Information Management & Business Analytics April 3rd 2014 Instructions Data Results C1 C2 C3 C4 C5 C6 C7 C8C1 C2 C3 C4 C5 C6 C7 C8 Dynamic In-Memory In-memory columnar processing with dynamic movement of data from storage Actionable Compression Patented compression technique that preserves order so data can be used without decompressing Parallel Vector Processing Multi-core and SIMD parallelism (Single Instruction Multiple Data) Data Skipping Skips unnecessary processing of irrelevant data Encoded “A query that takes hours on a 120 node Teradata system runs in seconds on DB2 with BLU Acceleration on a 24 core system.” Beta Test Client Why is DB2 with BLU Acceleration Different
  8. 8. Information Management & Business Analytics April 3rd 2014 © 2013 IBM Corporation8 Benefits of Cognos BI and DB2 with BLU Acceleration  18X Faster Cube Loading1 provides more timely information – Can refresh cubes more often – In one test, 1TB dynamic cube load took around 9.5 hours without BLU Acceleration and 30 min with BLU.  14X Faster Click Through Performance2 – More data in memory to improve performance of detailed query drill-downs – When data not found in Cognos dynamic cube, system looks for the data in BLU Acceleration table – also in memory – Result is significant performance improvements  Storage savings – Use of actionable compression – use data in compressed format – BLU Acceleration requires less database objects like indexes and MQTs that can often take up considerable amounts of space even when compressed  Simplicity – BLU Acceleration tables don’t need indexes or MQTs that have to be created and/or tuned – Just create the table, load data and run reports – Tools recommend which tables should be converted to BLU for maximum performance 1. To fill the Cognos Dynamic Cube aggregate cache, we saw an 18X improvement between DB2 10.5 and 10.1. We went from 9.5 hours to load the cache using DB2 10.1 compared with less than 30 minutes to load the cache using DB2 10.5 with BLU acceleration. 2. To further understand the benefits of using BLU acceleration with Cognos Dynamic Cubes, we isolated Cognos report queries against DB2 10.5 and DB2 10.1. These queries are examples of the SQL that would be run when a report has to query the database directly, rather than leveraging the in-memory aggregate cache. On average, the report query workload showed a 10x improvement. From 100 seconds to 10 seconds. *Performance is based on measurements and projections using standard IBM benchmarks in a controlled environment. The actual throughput or performance that any user will experience will vary depending upon many factors, including considerations such as the amount of multiprogramming in the user's job stream, the I/O configuration, the storage configuration, and the workload processed. Therefore, no assurance can be given that an individual user will achieve results similar to those stated here.
  9. 9. Information Management & Business Analytics April 3rd 2014 Cognos and Netezza a blazing combination © 2013 IBM Corporation9 1. Interactive analysis – engaging self-service interfaces 2. Enterprise scalability – supports thousands of users 3. Compelling visualizations – on the web, mobile, or emailed 4. Optimized queries – intelligently balances local and remote data processing 5. No wait time – instantaneous responses when in-memory cache is leveraged C O G N O S + Blazing Results= PureData System for Analytics 85+ Joint Customers 5 reasons to use Cognos BI with the Netezza
  10. 10. Information Management & Business Analytics April 3rd 2014 UK Examples of Netezza and Cognos customers  Greene King  Ace Insurance  Coventry Building Society
  11. 11. Information Management & Business Analytics April 3rd 2014 11  Lots of data: 250 GB– 1.000 TB  New data mart project in development  Lots of complex and ad hoc queries  Encountering performance challenges  Price sensitive  Old technology installations: e.g. Sybase, HP NeoView and Red Brick customers (end-of-life concerns)  Mid-range Oracle customers: Exadata and all Oracle DW BI projects  Limited IT-resources – need for simplicity  Industry focus:  Digital Media  Born-on-the-Web  Data Aggregators  Retailers  Financial Services  Life Sciences  Management unable to answer important questions from existing data warehouse  Exploiting information for competitive advantage  Users want answers in seconds and minutes (SLA’s)  Business needs to analyze up-to- date data all the time Netezza buying indicators Technology side Business side
  12. 12. Information Management & Business Analytics April 3rd 2014 InfoSphere portfolio and Cognos  Value proposition - InfoSphere & Cognos: – Ensure highest quality data for trusted Cognos reports (Data Quality solution) – Know what information is on your reports and where it came from (Business Information Exchange solution) – Make decisions based on up-to-date information (Data Replication solution) – Expand support for broader enterprise data access (Data Integration)
  13. 13. Information Management & Business Analytics April 3rd 2014 Cognos Data Manager  The Cognos Data Manager (DM) product – low cost, simple to deploy and use ETL tool – developed to fulfil the needs of feeding data to the Cognos cubes and schemas  It has worked well but is not as comprehensive as the InfoSphere Portfolio  There will be clients who need a more powerful solution  Chance for Cognos and IM partners to work together to identify opportunities
  14. 14. Information Management & Business Analytics April 3rd 2014 Big Data/Information Management Mark Chandler Big Data & Information Management Channel Manager Email: mark.chandler@uk.ibm.com Mobile: 07738 310900

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