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

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. 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. 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. Information Management & Business Analytics April 3rd 2014
Cognos & DB2

5. Information Management & Business Analytics April 3rd 2014

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. 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. 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. 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. Information Management & Business Analytics April 3rd 2014
UK Examples of Netezza and Cognos customers
 Greene King
 Ace Insurance
 Coventry Building Society

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. 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. 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. 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