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© 2012 Forrester Research, Inc. Reproduction Prohibited 1 © 2009 Forrester Research, Inc. Reproduction Prohibited
Agile Business Intelligence (BI) and Data Virtualization
Boris Evelson, Vice President, Principal Analyst
© 2012 Forrester Research, Inc. Reproduction Prohibited 2
Earlier generation BI and DW just don’t cut it anymore
Best practices Next-gen
technologies
Criticality
Scalability
Complexity
Low penetration
© 2012 Forrester Research, Inc. Reproduction Prohibited 3
Traditional BI is complex
Source: October 20, 2010, “The Forrester Wave™: Enterprise Business Intelligence Platforms, Q4 2010” Forrester report
Data Information
80% 20%
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The Four V’s Determine When Big Data Should Be Considered
Source: September 2011 “Expand Your Digital Horizon With Big Data”
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Traditional BI presents IT/business alignment challenges
Flexibility and agility Operational risk
management
Business IT
Reacting Planning
Interaction Requirements-gathering
Business requirements Standards
Analysis and Discovery Analysis
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Base: 1092 packaged-application decision-makers at firms with over 19 employees.
*Base: 782 custom software development decision-makers at firms with over 19 employees.
(Percentages do not total 100 because of rounding)
Source: Forrsights Software Survey, Q4 2011.
What are your firm's plans to adopt business intelligence software?
2%
3%
33%
12%
17%
13%
20%
3%
27%
16%
26%
18%
11%
Don't know
Decreasing / scaling back
Expanding / upgrading implementation
Developed/implemented, not expanding
Planning to develop/implement
Interested but no plans
Not interested
Packaged applications Custom development*
60%
28%
BI and analytics are hot!
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Organizations that use BI show increased levels of maturity, but it’s still a long road ahead
†Base: 173 technology professionals familiar with their respective organization’s BI efforts
Overall maturity 2.75
Governance and ownership 3.25
Organization 2.81
Processes 2.65
Data and technology 2.82
Measurement and adjustment 2.34
Keeping up with the latest trends 2.07
†Source: Q4 2010 Global BI Maturity Online Survey
BI Maturity is evaluated on a scale of 1 to 5 (low to high)
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Anecdotal evidence suggests that BI and analytics penetration levels in an average enterprise are still very low
Source: Boris Evelson, “Poll: What % of your company workers use traditional BI apps?” Boris Evelson’s Blog For
Business Process Professionals, April 24, 2011 (http://blogs.forrester.com/node/3974/results)
Percent of workers using enterprise BI applications
Pe
rce
nt
of
org
an
iza
tio
n
45%
19%
13%
23%
0%
10%
20%
30%
40%
50%
<6% 7%-10% 11%-19% >20%
“What percent of your company workers use traditional BI apps?”
In 64% of enterprises <10% of workers use BI
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Agile software development methodology by itself does not work well for BI
Agile relies on quick prototypes. Traditional BI technology
(RDBMS) does not lend itself to prototyping.
Agile is code-centric.
BI is data-centric.
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Forrester expands the definition of Agile – “democratized” - BI
Forrester defines Agile BI as:
An approach that combines
processes, methodologies,
organizational structure, tools, and
technologies that enable strategic,
tactical, and operational decision-
makers to be more flexible and
more responsive to the fast pace
of business and regulatory
requirement changes.
Source: March 31, 2011, “Trends 2011 And Beyond: Business Intelligence” Forrester report
Agile BI
3. Next-gen technology
2. Organizational and process best
practices
1. Software development methodology
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Agile development methodology
Liaisons, business analysts Face-to-face business
participation
Processes Interactions
Specifications Prototypes (virtualization)
Plan Reacting to change
Tra
ditio
na
l
Agile
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Start with organizational best practices
Insist on business
ownership and
governance. Emphasize
organization and
cultural change
management. Decouple data
preparation and data
usage. Treat front- and
back-office BI
requirements and
users differently. Establish hub-and-
spoke organizational
model.
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Follow up with process best practices
Use a combination
of top-down and
bottom-up
approaches. Use Agile
development
methodology. Enable BI self-
service for end
users.
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Base it all on four key categories of next-gen BI technologies
Source: March 31, 2011, “Trends 2011 And Beyond: Business Intelligence” Forrester report
Auto information discovery
Contextual BI
Integrated full lifecycle
BI on BI
Data sources
Data and content
Disk and streaming
Historical and predictive
Complex data structures
Metadata
Within processes
Within Information Workspace
Self service
SaaS
Mobile
Offline
Exploration and discovery
Adaptive data models
Big data
Unlimited dimensionality –
Advanced Data Visualization
* Where data virtualization plays a role
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A single data model cannot support all decision types – need a mixed environment
Source: July 2009, “Fit Your Data Architecture To Your Analytical Needs” Forrester report
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Data Latency And Complexity Capabilities Of Various Analytical Data Architectures
Source: July 2009, “Fit Your Data Architecture To Your Analytical Needs” Forrester report
Data
virtualization
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Key Analytical Data Architecture Decision Drivers
Source: July 2009, “Fit Your Data Architecture To Your Analytical Needs” Forrester report
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Key Analytical Data Architecture Decision Drivers (Cont.)
Source: July 2009, “Fit Your Data Architecture To Your Analytical Needs” Forrester report
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Key Analytical Data Architecture Decision Drivers (Cont.)
Source: July 2009, “Fit Your Data Architecture To Your Analytical Needs” Forrester report
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When and why Forrester recommends data virtualization
All enterprises have
multiple BI platforms
Push as much BI data access
functionality (queries, joins,
metrics, aggregates) into a single
data virtualization layer
Single EDW is not
practical, agile or flexible
New data sources may
come (very often) and go
Put data virtualization front and
center of provisioning (and
deprovisioning) data sources
Complement EDW with data
virtualization for flexibility and
agility
BI apps do not have an
exclusive on data access
Standardize data access for BI
and for OLTP apps. Minimize
data replication
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Choosing data virtualization technology: January 2012 “The Forrester Wave™: Data Virtualization, Q1 2012”
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Thank you
Boris Evelson
+1 617.613.6297
bevelson@forrester.com
http://blogs.forrester.com/boris_evelson
Twitter: @bevelson
www.forrester.com