The Briefing Room with Shawn Rogers and Composite Software Slides from the Live Webcast on May 15, 2012 Everyone wants more data these days, though often for different reasons. Business analysts, data scientists and front-line workers all know the value of having that extra piece of information. The big question remains -- how can all these needs be supported without taxing IT and without breaking the bank? And how can the worlds of traditional Business Intelligence, Big Data Analytics and Transaction Systems combine to improve business outcomes? In this episode of The Briefing Room, veteran Analyst Shawn Rogers of Enterprise Management Associates explains what is needed to take advantage from today's hybrid data ecosystem. He'll be briefed by Bob Eve of Composite Software who will explain how innovative enterprises are using data virtualization to gain insight across these worlds and doing so with greater agility and lower costs. For more information visit: http://www.insideanalysis.com Watch us on YouTube: http://www.youtube.com/playlist?list=PL5EE76E2EEEC8CF9E

1. Tuesday, May 15, 12

2. Eric.kavanagh@bloorgroup.com
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Tuesday, May 15, 12

3. Reveal the essential characteristics of enterprise
software, good and bad
Provide a forum for detailed analysis of today’s
innovative technologies
Give vendors a chance to explain their product to
savvy analysts
Allow audience members to pose serious questions...
and get answers!
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Tuesday, May 15, 12

4. May: Analytics
June: Intelligence
July: Governance
August: Analytics
September: Integration
October: Database
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Tuesday, May 15, 12

5. Ultimately analytics is about businesses making optimal
decisions, although the range of technologies that inhabit
this area is wide: statistical analysis, data mining, process
mining, predictive analytics, predictive modeling, business
process modeling and additionally complex event
processing.
With the advent of big data, analytics has become “big
analytics” with organizations diving into large heaps of data
that previously was not available or usable.
Part of the challenge is to be able to manage the data flow
so that power users and analytics users have the data they
need in the right place at the right time.
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Tuesday, May 15, 12

6. Shawn Rogers is Vice President Research
for Business Intelligence at Enterprise
Management Associates a leading
analyst and consulting firm. Shawn is
an international speaker and has more
than 19 years of hands-on IT experience.
Prior to joining EMA he co-founded the
BeyeNETWORK, a global online
publication covering business
intelligence, data warehousing,
performance management and data
integration. He was also a partner at
DMReview magazine (now Information
Management) and has held various
executive level positions with
technology companies.
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Tuesday, May 15, 12

7. Enterprise class data integration platform
Innovative data virtualization solution to the
data integration problem
High performance
Agile relatively low cost solution
Rapid development with quick iterations
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Tuesday, May 15, 12

8. Bob Eve has been Composite Software's
EVP of Marketing since 2006. While at
Composite, Bob helped define the Data
Virtualization category and position
Composite as the gold standard in that
market. Prior to Composite, Bob held
executive level marketing and business
development roles at leading
enterprise software companies such as
Informatica, Mercury Interactive,
PeopleSoft, and Oracle. Bob holds a MS
degree in Management from the
Massachusetts Institute of Technology
and a BS degree in Business
Administration from the University of
California at Berkeley.
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Tuesday, May 15, 12

9. When Worlds Collide:
Intelligence, Analytics &
Operations
The Briefing Room with
Shawn Rogers and
Composite Software
Robert Eve
EVP Marketing
reve@compositesw.com

10. Agenda
Why big data analytics, mobility and cloud
computing are breaking traditional data
integration paradigms
How data virtualization increases business and
IT agility
Proven paths to data virtualization success
2
© 2012 Composite Software, Inc. / Composite Proprietary

11. Business and Technology Drivers – Big Data Analytics,
Mobility & Cloud
IBM Global CIO Survey
2011
3
© 2012 Composite Software, Inc. / Composite Proprietary

12. Data Warehouses Met Traditional Integration Needs
One place to go
Business view of the
data Agility Meter
Data Warehouses
and Marts
4
© 2012 Composite Software, Inc. / Composite Proprietary

13. But Business Required Operational Data As Well
Up-to-the-minute data
from transactional
sources is also required
Agility Meter
New integration
techniques are
needed…ODS, CDC,
Data Federation…
Transactional & Data Warehouses Enterprise
Operational Stores and Marts Applications
5
© 2012 Composite Software, Inc. / Composite Proprietary

14. Organizations Then Adopted New Information Management
Technologies To Address New Business Needs
The rise of fit-for-
purpose analytic data
stores creates more
Agility Meter
data silos
The emergence of
cloud-resident
applications introduces
new integration
challenges
Analytic Stores Transactional & Data Warehouses Enterprise SaaS
and Sandboxes Operational Stores and Marts Applications Applications
6
© 2012 Composite Software, Inc. / Composite Proprietary

15. While New IT Paradigms Arose Creating Even More
Complex Integration Landscapes
Web services require
new data integration
protocols and techniques
Agility Meter
Big Data analytic
processing and storage
reset tooling and
integration paradigms
Analytic Stores Transactional & Data Warehouses Enterprise SaaS “Big” Data
Web
Services and Sandboxes Operational Stores and Marts Applications Applications and NoSQL
7
© 2012 Composite Software, Inc. / Composite Proprietary

16. And BYOD Became the New Normal
Mobile devices
diversify
consumers and
Agility Meter
add network
latency challenges
Analytic Stores Transactional & Data Warehouses Enterprise SaaS “Big” Data
Web
Services and Sandboxes Operational Stores and Marts Applications Applications and NoSQL
8
© 2012 Composite Software, Inc. / Composite Proprietary

17. Data Virtualization Hides Complexity to Provide Business
Insight with Agility
One “virtual”
place to go
Business “view” Agility Meter
of the data
Data Virtualization Platform
Abstract Federate Optimize
Analytic Stores Transactional & Data Warehouses Enterprise SaaS “Big” Data
Web
Services and Sandboxes Operational Stores and Marts Applications Applications and NoSQL
9
© 2012 Composite Software, Inc. / Composite Proprietary

18. Agenda
Why big data analytics, mobility and cloud
computing are breaking traditional data
integration paradigms
How data virtualization increases business
and IT agility
Proven paths to data virtualization success
10
© 2012 Composite Software, Inc. / Composite Proprietary

19. Enterprise-Scale Data Virtualization Platform
Customer Governance,
Business Human Capital Mergers & Single View of Supply Chain SAP Data
Experience Risk &
Intelligence Management Acquisitions Enterprise Data Management Integration
Management Compliance
Composite 6 Data Virtualization Platform
Development Runtime Server Management
Environment Environment Environment
Discovery Manager
Studio Composite Information Server Monitor
PerformancePlus
Active Cluster
Adapters
XML
Packaged Apps RDBMS Excel Files Data Warehouse OLAP Cubes Hadoop / “Big Data” XML Docs Flat Files Web Services
11
© 2012 Composite Software, Inc. / Composite Proprietary

20. One “Virtual” Place Go
12
© 2012 Composite Software, Inc. / Composite Proprietary

21. Business “View” of the Data
Source: Forrester June 15, 2011, “Data Virtualization Reaches Critical Mass” Forrester report
13
© 2012 Composite Software, Inc. / Composite Proprietary

22. Agenda
Why big data analytics, mobility and cloud
computing are breaking traditional data
integration paradigms
How data virtualization increases business and
IT agility
Proven paths to data virtualization success
14
© 2012 Composite Software, Inc. / Composite Proprietary

23. Use A Proven Data Virtualization Vendor
Ten of the Top Twenty Global Money Center Banks Major Communications and Technology Vendors
Six of the Top Ten Pharmaceutical Companies Government Agencies including the World’s Largest
IT Organization, the U.S. Army
Four of the Top Five Integrated Energy Companies
Composite Data Virtualization
Financial Federal Media /
Life Sciences High Tech Energy
Services Government Comm.
15
© 2012 Composite Software, Inc. / Composite Proprietary

24. Seek Out The Data Virtualization Domain Experts
Company Domain Deployment
Comcast Directory Ownership change
Services processing
Compassion Enterprise wide Ministry Information
International Library
Fortune 50 Procurement Integrated procurement
Computer reporting system
Manufacturer
Fortune 50 Financial Wholesale Bank Support for mergers and
Services Firm acquisitions, new
business opportunities
Global 100 Energy Upstream Virtual data warehouse to
Company Operations support BI reporting and
analytics
Global 100 Financial Investment Bank Data Vault
Services Firm Division
Northern Trust Corporate and Investment Operations
Institutional Outsourcing client
Services reporting platform
Business Unit
NYSE Euronext Enterprise wide Virtual data warehouse for
post-trade reporting and
analysis
Pfizer Worldwide Project portfolio database
Pharmaceutical
Sciences (R&D)
Qualcomm Enterprise wide Multiple applications
16
© 2012 Composite Software, Inc. / Composite Proprietary

25. Self Fund Your Investment
Massive transaction volumes
$4.5 million saved on first project
$2.2 million saved on first five projects
24 projects in 2 years
Zero downtime customer care apps
$ thousands per day in cost savings
17
© 2012 Composite Software, Inc. / Composite Proprietary

26. For More Information
www.compositesw.com www.datavirtualizationcafe.com
18
© 2012 Composite Software, Inc. / Composite Proprietary

27. Twitter Tag: #briefr
Tuesday, May 15, 12

28. When Worlds Collide: Intelligence,
Analytics and Operations
Shawn P. Rogers
Enterprise Management Associates
Vice President Research Business Intelligence / Data
Warehousing
srogers@enterprisemanagement.com
May 15, 2012
© 2012 Enterprise Management Associates, Inc.
Tuesday, May 15, 12

29. The Drivers of Change
• Maturing User Community
• Workloads and Demands – Reporting to Advanced Analytics
• Consumer shift, democratization and self service
• New Technology
• Introduction of new technologies
• More powerful technology
• Economics
• Enterprise level commodity hardware
• Open Source frameworks
• Business Intelligence is recession resistant and proven
• Valuable Data Types
• Move from Structured SQL driven analysis - new alternatives
• Sophisticated analysis of new data – Sensor, Machine, Social
11 © 2012 Enterprise Management Associates, Inc.
Tuesday, May 15, 12

30. Drivers of Change
• The EDW Under Pressure
• A critical component of success
• Difficulty answering the demands of change
 Users, technology, economics and new data
• Analytics beyond the data warehouse
12 © 2012 Enterprise Management Associates, Inc.
Tuesday, May 15, 12

31. Drivers of Change
• The EDW Under Pressure
• A critical component of success
• Difficulty answering the demands of change
 Users, technology, economics and new data
• Analytics beyond the data warehouse
Time to live in the now….not the was.
12 © 2012 Enterprise Management Associates, Inc.
Tuesday, May 15, 12

32. Hybrid Data Ecosystem
• Extension of Traditional Data Environments
• Workload Management
 Matching data and complex workloads to the best possible platforms
 Flexible, powerful and economically sound.
• Platforms
 Computing Platforms
 Enterprise Data Warehouse
 Data Marts
 Operational Systems
 Analytic Platforms
 Big Data (Hadoop, Key/Value, Graph data stores)
 Cloud-based Solutions
13 © 2012 Enterprise Management Associates, Inc.
Tuesday, May 15, 12

33. Hybrid Data Ecosystem
 Delivery Platforms
 Desktop
 Internet/Web
 Mobile
 Collaborative Solutions
• Data Integration Tier
 Innovation and agility abound
 Makes the case for enterprise wide implementations
 You can’t always move the data – Cloud and Big Data especially
• Data Management Tier
 Weakness across ecosystem
 Opportunity for innovation
 Runs in the face of big stack vendors
 Beware of silo’s
14 © 2012 Enterprise Management Associates, Inc.
Tuesday, May 15, 12

34. Hybrid Data Ecosystem - Platforms
Enterprise Data
Warehouse
(RDBMS)
15 © 2012 Enterprise Management Associates, Inc.
Tuesday, May 15, 12

35. Hybrid Data Ecosystem - Platforms
Enterprise Data
Warehouse
(RDBMS)
Data Marts
15 © 2012 Enterprise Management Associates, Inc.
Tuesday, May 15, 12

36. Hybrid Data Ecosystem - Platforms
Operational Data
Enterprise Data
Warehouse
(RDBMS)
Data Marts
15 © 2012 Enterprise Management Associates, Inc.
Tuesday, May 15, 12

37. Hybrid Data Ecosystem - Platforms
Big Data
Operational Data
Frameworks
Enterprise Data
Warehouse
(RDBMS)
Data Marts
15 © 2012 Enterprise Management Associates, Inc.
Tuesday, May 15, 12

38. Hybrid Data Ecosystem - Platforms
Big Data
Operational Data
Frameworks
Enterprise Data
Warehouse
(RDBMS)
Data Marts
Analytic
Platforms
15 © 2012 Enterprise Management Associates, Inc.
Tuesday, May 15, 12

39. Hybrid Data Ecosystem - Platforms
Big Data
Operational Data
Frameworks
Enterprise Data
Warehouse
(RDBMS)
Cloud Data
Data Marts
Analytic
Platforms
15 © 2012 Enterprise Management Associates, Inc.
Tuesday, May 15, 12

40. Hybrid Data Ecosystem - Platforms
Big Data
Operational Data
Frameworks
Enterprise Data
010 Warehouse
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010 10
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010 101
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010 1 01 01
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0101001010101010
101 10 1
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010
01 01 101
101 010
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101 10 101 010
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1 10 10
010
101 Cloud Data 01
01
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Data Marts
Analytic
Platforms
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41. Tuesday, May 15, 12

42. Managing Hybrid Data Ecosystems for
Performance
• A balanced attack - use all of the tools at your disposal
• Understand the workload complexity and plan accordingly
• Utilize the best data sources combined with best platform
• Only move the data when necessary
 Accept that some data is better off not moved
 Economics of moving data – push down queries
• Create value by combining data from where ever necessary
17 © 2012 Enterprise Management Associates, Inc.
Tuesday, May 15, 12

43. Agility is often discussed with DV. Explain where that comes in
and how it makes an organization more agile?
How do you see DV enabling companies that are embracing a
Hybrid Data Ecosystem? Why is data integration part of this
paradigm shift?
Is DV technology fast enough to keep pace with the sophisticated
needs of these maturing analytics users?
How do address highly distributed data especially when it’s
geographically remote and has inherent latency?
What’s changed in DV technology since the 90’s when similar
technology was labeled virtual DW’s, Federation and EII in the
2000’s and failed to get traction with DW purists?
Should companies could/should attempt to implement DV
company wide or are point solutions the best way to go?
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Tuesday, May 15, 12

44. When is DV not a good answer to data integration challenges?
Where does Data Quality fit into DV? Does Composite offer DQ
features? Is it required?
Big Data has everyone’s attention is it really a significant
opportunity? Is it for Hadoop only?
How does Composite go beyond simple Hadoop connectors to
assist companies with Big Data?
How do you work with Analytic Platforms to go beyond simple
integration?
What’s next for DV? Are their other connection/integration
points working their way into the data ecosystem?
Can DV really support the needs of self-service analytic users or
power users?
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Tuesday, May 15, 12

45. Tuesday, May 15, 12

46. May: Analytics
June: Intelligence
July: Governance
August: Analytics
September: Integration
October: Database
Twitter Tag: #briefr
Tuesday, May 15, 12

47. Tuesday, May 15, 12