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© 2015 Denodo
Craig LeClaire
VP, Principal Analyst
Megan Burns
VP, Principal Analyst
Cory Munchbach
Analyst
Holger Kisker, Ph.D.
VP and Research Director
Session 1
CIO’s Must Enable Business Agility
via Modern Data Management in the
Age of the Customer
Session 2
Understanding the Customer
Experience Ecosystem to Succeed in
the Age of the Customer
Session 3
Build a Contextual Marketing
Engine and Fuel it with Data
Session 4
Business Agility Must Be Based
on a New Flexible and Agile Data
Approach
Data Virtualization for Business Intelligence and
Business Agility in the Age of the Customer
Four sessions providing insights and best
practices for the Age of the Customer
WEBINAR SERIES featuring FORRESTER RESEARCH
© 2015 Denodo
Data Virtualization for Business Intelligence and
Business Agility in the Age of the Customer
Suresh Chandrasekaran
Senior VP, Denodo
© 2015 Denodo
Business Agility Must Be Based on
a New Flexible and Agile Data
Approach
Holger Kisker, Ph.D.
VP and Research Director
SESSION 4
Making Leaders Successful
Every Day
Business Agility Must Be Based
on a New Flexible and Agile Data
Approach
Holger Kisker, Ph.D.
Vice President & Research Director
Data initiatives are the most important tech
investments
Source: Forrsights Software Survey, Q4 2013
Base: 2,074 technology executives and technology decision makers
57% of decision
makers rank data
projects the most
important
investment in
their company
7%
16%
15%
18%
20%
24%
5%
12%
18%
17%
16%
33%
Social related projects
Mobile related projects
Cloud related projects
Systems of engagement
applications
Systems of record
applications
Data related projects
2nd Priority
Top Priority
Please rank the following technologies according to their
importance and investment within your firm?
© 2013 Forrester Research, Inc. Reproduction Prohibited 7
The main driver is to better decisions
What are the most important goals/drivers your organization considers when planning or
orchestrating your business intelligence strategy?
10%
21%
27%
28%
29%
37%
42%
43%
53%
Achieve better business transparency
Develop better products and services
Improve business planning
Gain competitive advantage
Ensure compliance and reduce risks
Improve data quality and consistency
Improve customer interaction and
satisfaction
Monitor, improve, and optimize process
performance
Make better informed business
decisions
Base: 249 North American business decision-makers
Respondents answering “don’t know” are not shown
Source: Global Data and Analytics Survey, 2014
Business
growth
drivers
Technical
& control
drivers
Turn Data Into Business Insights
More Deeper For Everyone
Deeper Insights
More Data
For Everyone
© 2014 Forrester Research, Inc. Reproduction Prohibited
Culture
• Data treated as
an asset
• Data-driven
• Data shared
across silos
Capabilities
• Advanced data
management,
delivery and
analysis
Competency
• Technology skills
• Analytical skills
• New approach to
data governance
• Agile processes
Success
Ingredients To A New Flexible And Agile Data Approach
© 2014 Forrester Research, Inc. Reproduction Prohibited
Culture
• Data treated as
an asset
• Data-driven
• Data shared
across silos
Competency
• Technology skills
• Analytical skills
• New approach to
data governance
• Agile processes
Capabilities
• Advanced data
management,
delivery and
analysis Success
Ingredients To A New Flexible And Agile Data Approach
© 2014 Forrester Research, Inc. Reproduction Prohibited
Choose The Appropriate Data Management Technology
Highlytopolystructured
Batch to real time
Velocity
Variety
Scalable NoSQL
In-memory
Streaming
Standard SQL
apppliance
Structured
historical data
Int./ext.
polystructured
data
In-time
dynamic data
Real-time data
in motion
© 2014 Forrester Research, Inc. Reproduction Prohibited
Not all data needs to fly First Class
Front
Rear
© 2014 Forrester Research, Inc. Reproduction Prohibited
Data
Science
Workbench
Hadoop
Streaming
SQL
Datawarehouse
Application
In-Memory
Datawarehouse
Any Data
Sources
A new approach to architecture –
hub-and-spoke (example)
Advanced data analytics for
deeper Insights
Advanced data management
technologies to use more data
Advanced data delivery technologies
to leverage & share insights
© 2014 Forrester Research, Inc. Reproduction Prohibited
Data About The Future Is The Most Valuable!
10%
14%
13%
15%
14%
18%
18%
23%
18%
21%
28%
29%
37%
31%
27%
28%
31%
5%
7%
8%
7%
10%
8%
12%
11%
17%
15%
22%
22%
26%
36%
41%
44%
53%
Unstructured external data
Social network data
Consumer mobile device data
Weblog data from publically facing sites
Sensor data other than mobile devices
Video, imagery & audio
Partner data
Third party data sets
Scientific data
Log data from corporate systems
Product data
Unstructured internal data
Home-grown data stored in spreadsheets or other…
Transactional data from corporate custom build apps
Customer data
Transactional data from corporate packaged apps
Planning, budgeting, forecasting data
4 5. very important
Base: 634 Business Intelligence users and planners
“How important are the following data types to your firm's overall business strategy?”
Answers 4 and 5 on a scale where 1- not at all important and 5 – very important
Source: Forrsights BI/Big Data Survey, Q3 2012
Data value
$$
© 2014 Forrester Research, Inc. Reproduction Prohibited
Traditional Reporting
Predictive Analytics
You know nothing about your customer
Deeper Customer Insights With Advanced
Analytics
Why did he buy our product?
What is he going to need next?When will he need support?
Where is he right now?
Advanced data analytics for
deeper Insights
Advanced data management
technologies to use more data
Advanced data delivery technologies
to leverage & share insights
© 2014 Forrester Research, Inc. Reproduction Prohibited
Visual display and self-service are key
Image source & copyright: http://www.cloudred.com/labprojects/nyctrees/
Image source & copyright: Microsoft
© 2014 Forrester Research, Inc. Reproduction Prohibited
Culture
• Data treated as
an asset
• Data-driven
• Data shared
across silos
Capabilities
• Advanced data
management,
delivery and
analysis
Competency
• Technology skills
• Analytical skills
• New approach to
data governance
• Agile processes
Success
Ingredients To A New Flexible And Agile Data Approach
© 2014 Forrester Research, Inc. Reproduction Prohibited
New hub-and-spoke architecture
Data
Science
Workbench
Hadoop
Streaming
SQL
Datawarehouse
Application
In-Memory
Datawarehouse
Any Data
Sources
© 2014 Forrester Research, Inc. Reproduction Prohibited
How Much Hadoop Skills Do You Need?
Very few specific skills:
Using „enterprise-ready“
Hadoop solutions, (e.g.
MapR, Cloudera,
Hortenworks)
Some specific skills:
Leverage OpenSource
Ecosystem (e.g. Pig,
Hive, HBase)
Native Hadoop
integration: Java coding
in distributed file system
with map-reduce
© 2014 Forrester Research, Inc. Reproduction Prohibited
› Advanced analytics apply
data models based on
mathematic-statistical
methodologies & algorithms
• What is the right
algorithm?
• Adjust the model to
reflect business reality
Data Scientist: Sexiest Job of the 21st Century
› Vendors start to close the
skills gap with pre-
packaged solutions and
data services
› A team-based approach is
essential: tech management
& data scientist & business
& other experts
Source: http://www.practicaldb.com/demos/
Build
Integrate
UseShare
Self-
Service
Skills &
Processes
© 2014 Forrester Research, Inc. Reproduction Prohibited
Culture
• Data treated as
an asset
• Data-driven
• Data shared
across silos
Capabilities
• Advanced data
management,
delivery and
analysis
Competency
• Technology skills
• Analytical skills
• New approach to
data governance
• Agile processes
Success
Ingredients To A New Flexible And Agile Data Approach
© 2014 Forrester Research, Inc. Reproduction Prohibited
Business outcome
Data sources
Deeper insights
More data
For everyone
What business value
do we want?
Who needs what
insights for this?
What analysis tools
do we need?
How can we
manage all the data
needed?
What data
do we have?
How can
we process that
data?
What can
we learn from this
data?
How
do we deliver those
insights?
Bottom-uptechnology-driven
Top-downbusiness-driven
What business value
can we create?
What data sources
do we need?
There’s no single right way to plan
Data delivers benefits on different levels
Strategic Benefits
(e.g. increased asset value on
balance sheet, reduced risk
exposure, improved
performance, better planning)
LoB Benefits (e.g.
downtime, operational cost,
asset utilization, improved
quality, production
performance)
User Benefits
(e.g. decision support,
reduced search time,
satisfaction, self-service,
mobile support)
IT Benefits
(e.g. data quality, data
utilization, improved models,
real-time, improved SLAs)
„Data Will Become
An Asset On The
Balance Sheet“
© 2014 Forrester Research, Inc. Reproduction Prohibited
Everybody can benefit from big data
Base: 1,077 North American and European
Software decision-makers who are using or
Planning to use big data (20+ employees)
“What groups or departments are currently using big data/planning to use big data in
2014?”
Source: Forrester’s Forrsights Software Survey, Q4 2013
Operations
38%
(e.g., supply-demand)
Marketing
34%
(e.g., campaigns)
IT analytics
58%
(e.g., network secure)
Finance
31%
(e.g., risk exposure)
Sales
36%
(e.g., cross-/upsell)
Research
32%
(e.g., simulation)
Customer service
31%
(e.g., segmentation)
Manufacturing
20%
(e.g., process opt.)
GRC
14%
(e.g., auditing)
Product
development28%(e.
g., social feedback)
Logistic and distr.
27%
(e.g., route opt.)
Human resources
19%
(e.g., head hunting)
Procurement
17%
(e.g., best buy)
Supply chain
23%
(e.g., sourcing)
Other
3%
Don’t know
1%
Hadoop
Reporting
Process
Optimization
Data
Management
Data
Processing
Information
Usage
Data
Sources
EDW
Advanced
Analytics
Decision
Support
Engagement
Systems of
Customer
Engagement
In-Memory Streaming
Record
Systems of
Economy
Data
© 2014 Forrester Research, Inc. Reproduction Prohibited
Don’t end up in a (big) data zoo!
Image source & copyright: Teradata
Hadoop
Reporting
Process
Optimization
Data
Management
Data
Processing
Information
Usage
Data
Sources
EDW
Advanced
Analytics
Decision
Support
Engagement
Systems of
Customer
Engagement
In-Memory Streaming
Record
Systems of
Economy
Data
Hadoop
Reporting
Process
Optimization
Data
Management
Data
Processing
Information
Usage
Data
Sources
EDW
Advanced
Analytics
Decision
Support
Engagement
Systems of
Customer
Engagement
In-Memory Streaming
Record
Systems of
Economy
Data
Hadoop EDW Streaming
Engagement
Systems of
Record
Systems ofReporting Advanced
Analytics
Customer
Engagement Economy
DataDecision
Support
Process
Optimization
In-Memory
Data
Management
Data
Processing
Information
Usage
Data
Sources
Data
Sources
Data Virtualization
Data Virtualization
Discovery
Access
Manage
Monitor
Performance
Data
Sources
Data Virtualization
Manage
Unified Data
Governance
• Security
• Privacy
• Quality
• Standards
• Life Cycle
Access
Unified Data
Access to any
• Source
• Application
• Insight
• Employee
• Customer
• Business
Partner
Monitor
Unified Data
Monitoring
• BI on BI
• Compliance
• Health
• Business
Usage
Discovery
Finding the
nuggets
• Sources
• Pattern
• Insights
• Use Cases
• Business
Value
Performance
Optimized Data
Performance
• Workload
Optimization
• Cost
• Availability
• Usability
• Business
Managing the Complexity Of A Modern Data Architecture
Image source: Big Data World Congress (http://bigdatacongress.com/) and c1.staticflickr.com
((//c1.staticflickr.com/1/40/123900378_e668dd966e.jpg)
There is no single ‘best’
data Use Case; start your
own road map.
There is no single ‘best’
data technology; see what
fits your needs.
Don‘t create data silos;
think strategically and
put in place a flexible
platform & data
virtualization
Tech management recommendations
Thank you
Holger Kisker
hkisker@forrester.com
@hkisker
+49 69 959 29862
© 2015 Denodo
CDO / CIO new calling - Turn MORE
data into DEEPER business insights
for EVERYONE
Requires new capability, competency
and culture of data as an asset
Capabilities at 3 levels of data,
analytics, delivery of insights requires
variety of best of breed tools
Beware of increased complexities ,
solution silos, replicated data, Big
Data Zoo!
Agile data architecture across layers -
data source, management,
processing, delivery – to abstract,
hide complexity, deliver info faster
Forrester Take Aways Denodo Enablers
Fast data access; Information-as-a-
service; Agile integration
Organize canonical business entities
used across dimensions
Single View of Customer; Data
distribution across channels
Structured & unstructured; Internal
& external; Real-time; Self-Service;
Less replicated; Virtual
Unified data abstraction layer
democratizes access to single source
of truth across and beyond
organization boundaries
Agile Data Architecture – How Denodo drives it
© 2015 Denodo
 Access any source
 Make them look
homogeneous
 Pre-integrated graph of
information for users
 Build very rapidly
 Data services feed many
applications & users
ROI?
“..saved 1000s of
development hours”
“.. exceeded breakeven
expectations – smash through
it!”
“.. tackled business value for
more leverage, not IT cost”
Agile Data Architecture – Capital Markets Firm
© 2015 Denodo
Agile Data Architecture – Technology Firm
BI 2.0: Best of breed Complexity! Tamed by Data Virtualization
© 2015 Denodo
Data Virtualization - Two Approaches to Adopt
Solve
one/more
projects
Prove
value
Expand to
other use
cases
Reusability
and
scalability
Expand
enterprise-
wide
Enterprise
strategic
vision
Design for
scale and
support
Systemic
data
services
High value
use cases
first
Multiple
usage
patterns
Tactical
Approach
Enterprise-wide
Approach
People Process Technology
Hybrid
Approach
Possible
© 2015 Denodo
Q&A
© 2015 Denodo
Thank you!
Data Virtualization for Business Intelligence and
Business Agility in the Age of the Customer
Four sessions providing insights and best
practices for the Age of the Customer
WEBINAR SERIES featuring FORRESTER RESEARCH

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Business Agility Must Be Based on a New Flexible and Agile Data Approach

  • 1. © 2015 Denodo Craig LeClaire VP, Principal Analyst Megan Burns VP, Principal Analyst Cory Munchbach Analyst Holger Kisker, Ph.D. VP and Research Director Session 1 CIO’s Must Enable Business Agility via Modern Data Management in the Age of the Customer Session 2 Understanding the Customer Experience Ecosystem to Succeed in the Age of the Customer Session 3 Build a Contextual Marketing Engine and Fuel it with Data Session 4 Business Agility Must Be Based on a New Flexible and Agile Data Approach Data Virtualization for Business Intelligence and Business Agility in the Age of the Customer Four sessions providing insights and best practices for the Age of the Customer WEBINAR SERIES featuring FORRESTER RESEARCH
  • 2. © 2015 Denodo Data Virtualization for Business Intelligence and Business Agility in the Age of the Customer Suresh Chandrasekaran Senior VP, Denodo
  • 3. © 2015 Denodo Business Agility Must Be Based on a New Flexible and Agile Data Approach Holger Kisker, Ph.D. VP and Research Director SESSION 4
  • 5. Business Agility Must Be Based on a New Flexible and Agile Data Approach Holger Kisker, Ph.D. Vice President & Research Director
  • 6. Data initiatives are the most important tech investments Source: Forrsights Software Survey, Q4 2013 Base: 2,074 technology executives and technology decision makers 57% of decision makers rank data projects the most important investment in their company 7% 16% 15% 18% 20% 24% 5% 12% 18% 17% 16% 33% Social related projects Mobile related projects Cloud related projects Systems of engagement applications Systems of record applications Data related projects 2nd Priority Top Priority Please rank the following technologies according to their importance and investment within your firm?
  • 7. © 2013 Forrester Research, Inc. Reproduction Prohibited 7 The main driver is to better decisions What are the most important goals/drivers your organization considers when planning or orchestrating your business intelligence strategy? 10% 21% 27% 28% 29% 37% 42% 43% 53% Achieve better business transparency Develop better products and services Improve business planning Gain competitive advantage Ensure compliance and reduce risks Improve data quality and consistency Improve customer interaction and satisfaction Monitor, improve, and optimize process performance Make better informed business decisions Base: 249 North American business decision-makers Respondents answering “don’t know” are not shown Source: Global Data and Analytics Survey, 2014 Business growth drivers Technical & control drivers
  • 8. Turn Data Into Business Insights More Deeper For Everyone
  • 10. © 2014 Forrester Research, Inc. Reproduction Prohibited Culture • Data treated as an asset • Data-driven • Data shared across silos Capabilities • Advanced data management, delivery and analysis Competency • Technology skills • Analytical skills • New approach to data governance • Agile processes Success Ingredients To A New Flexible And Agile Data Approach
  • 11. © 2014 Forrester Research, Inc. Reproduction Prohibited Culture • Data treated as an asset • Data-driven • Data shared across silos Competency • Technology skills • Analytical skills • New approach to data governance • Agile processes Capabilities • Advanced data management, delivery and analysis Success Ingredients To A New Flexible And Agile Data Approach
  • 12. © 2014 Forrester Research, Inc. Reproduction Prohibited Choose The Appropriate Data Management Technology Highlytopolystructured Batch to real time Velocity Variety Scalable NoSQL In-memory Streaming Standard SQL apppliance Structured historical data Int./ext. polystructured data In-time dynamic data Real-time data in motion
  • 13. © 2014 Forrester Research, Inc. Reproduction Prohibited Not all data needs to fly First Class Front Rear
  • 14. © 2014 Forrester Research, Inc. Reproduction Prohibited Data Science Workbench Hadoop Streaming SQL Datawarehouse Application In-Memory Datawarehouse Any Data Sources A new approach to architecture – hub-and-spoke (example)
  • 15. Advanced data analytics for deeper Insights Advanced data management technologies to use more data Advanced data delivery technologies to leverage & share insights
  • 16. © 2014 Forrester Research, Inc. Reproduction Prohibited Data About The Future Is The Most Valuable! 10% 14% 13% 15% 14% 18% 18% 23% 18% 21% 28% 29% 37% 31% 27% 28% 31% 5% 7% 8% 7% 10% 8% 12% 11% 17% 15% 22% 22% 26% 36% 41% 44% 53% Unstructured external data Social network data Consumer mobile device data Weblog data from publically facing sites Sensor data other than mobile devices Video, imagery & audio Partner data Third party data sets Scientific data Log data from corporate systems Product data Unstructured internal data Home-grown data stored in spreadsheets or other… Transactional data from corporate custom build apps Customer data Transactional data from corporate packaged apps Planning, budgeting, forecasting data 4 5. very important Base: 634 Business Intelligence users and planners “How important are the following data types to your firm's overall business strategy?” Answers 4 and 5 on a scale where 1- not at all important and 5 – very important Source: Forrsights BI/Big Data Survey, Q3 2012 Data value $$
  • 17. © 2014 Forrester Research, Inc. Reproduction Prohibited Traditional Reporting Predictive Analytics
  • 18. You know nothing about your customer
  • 19. Deeper Customer Insights With Advanced Analytics Why did he buy our product? What is he going to need next?When will he need support? Where is he right now?
  • 20. Advanced data analytics for deeper Insights Advanced data management technologies to use more data Advanced data delivery technologies to leverage & share insights
  • 21. © 2014 Forrester Research, Inc. Reproduction Prohibited Visual display and self-service are key Image source & copyright: http://www.cloudred.com/labprojects/nyctrees/ Image source & copyright: Microsoft
  • 22. © 2014 Forrester Research, Inc. Reproduction Prohibited Culture • Data treated as an asset • Data-driven • Data shared across silos Capabilities • Advanced data management, delivery and analysis Competency • Technology skills • Analytical skills • New approach to data governance • Agile processes Success Ingredients To A New Flexible And Agile Data Approach
  • 23. © 2014 Forrester Research, Inc. Reproduction Prohibited New hub-and-spoke architecture Data Science Workbench Hadoop Streaming SQL Datawarehouse Application In-Memory Datawarehouse Any Data Sources
  • 24. © 2014 Forrester Research, Inc. Reproduction Prohibited How Much Hadoop Skills Do You Need? Very few specific skills: Using „enterprise-ready“ Hadoop solutions, (e.g. MapR, Cloudera, Hortenworks) Some specific skills: Leverage OpenSource Ecosystem (e.g. Pig, Hive, HBase) Native Hadoop integration: Java coding in distributed file system with map-reduce
  • 25. © 2014 Forrester Research, Inc. Reproduction Prohibited › Advanced analytics apply data models based on mathematic-statistical methodologies & algorithms • What is the right algorithm? • Adjust the model to reflect business reality Data Scientist: Sexiest Job of the 21st Century › Vendors start to close the skills gap with pre- packaged solutions and data services › A team-based approach is essential: tech management & data scientist & business & other experts
  • 27. © 2014 Forrester Research, Inc. Reproduction Prohibited Culture • Data treated as an asset • Data-driven • Data shared across silos Capabilities • Advanced data management, delivery and analysis Competency • Technology skills • Analytical skills • New approach to data governance • Agile processes Success Ingredients To A New Flexible And Agile Data Approach
  • 28. © 2014 Forrester Research, Inc. Reproduction Prohibited Business outcome Data sources Deeper insights More data For everyone What business value do we want? Who needs what insights for this? What analysis tools do we need? How can we manage all the data needed? What data do we have? How can we process that data? What can we learn from this data? How do we deliver those insights? Bottom-uptechnology-driven Top-downbusiness-driven What business value can we create? What data sources do we need? There’s no single right way to plan
  • 29. Data delivers benefits on different levels Strategic Benefits (e.g. increased asset value on balance sheet, reduced risk exposure, improved performance, better planning) LoB Benefits (e.g. downtime, operational cost, asset utilization, improved quality, production performance) User Benefits (e.g. decision support, reduced search time, satisfaction, self-service, mobile support) IT Benefits (e.g. data quality, data utilization, improved models, real-time, improved SLAs) „Data Will Become An Asset On The Balance Sheet“
  • 30. © 2014 Forrester Research, Inc. Reproduction Prohibited Everybody can benefit from big data Base: 1,077 North American and European Software decision-makers who are using or Planning to use big data (20+ employees) “What groups or departments are currently using big data/planning to use big data in 2014?” Source: Forrester’s Forrsights Software Survey, Q4 2013 Operations 38% (e.g., supply-demand) Marketing 34% (e.g., campaigns) IT analytics 58% (e.g., network secure) Finance 31% (e.g., risk exposure) Sales 36% (e.g., cross-/upsell) Research 32% (e.g., simulation) Customer service 31% (e.g., segmentation) Manufacturing 20% (e.g., process opt.) GRC 14% (e.g., auditing) Product development28%(e. g., social feedback) Logistic and distr. 27% (e.g., route opt.) Human resources 19% (e.g., head hunting) Procurement 17% (e.g., best buy) Supply chain 23% (e.g., sourcing) Other 3% Don’t know 1%
  • 32. © 2014 Forrester Research, Inc. Reproduction Prohibited Don’t end up in a (big) data zoo! Image source & copyright: Teradata
  • 35. Hadoop EDW Streaming Engagement Systems of Record Systems ofReporting Advanced Analytics Customer Engagement Economy DataDecision Support Process Optimization In-Memory Data Management Data Processing Information Usage Data Sources
  • 37. Data Sources Data Virtualization Manage Unified Data Governance • Security • Privacy • Quality • Standards • Life Cycle Access Unified Data Access to any • Source • Application • Insight • Employee • Customer • Business Partner Monitor Unified Data Monitoring • BI on BI • Compliance • Health • Business Usage Discovery Finding the nuggets • Sources • Pattern • Insights • Use Cases • Business Value Performance Optimized Data Performance • Workload Optimization • Cost • Availability • Usability • Business Managing the Complexity Of A Modern Data Architecture
  • 38. Image source: Big Data World Congress (http://bigdatacongress.com/) and c1.staticflickr.com ((//c1.staticflickr.com/1/40/123900378_e668dd966e.jpg)
  • 39. There is no single ‘best’ data Use Case; start your own road map. There is no single ‘best’ data technology; see what fits your needs. Don‘t create data silos; think strategically and put in place a flexible platform & data virtualization Tech management recommendations
  • 41. © 2015 Denodo CDO / CIO new calling - Turn MORE data into DEEPER business insights for EVERYONE Requires new capability, competency and culture of data as an asset Capabilities at 3 levels of data, analytics, delivery of insights requires variety of best of breed tools Beware of increased complexities , solution silos, replicated data, Big Data Zoo! Agile data architecture across layers - data source, management, processing, delivery – to abstract, hide complexity, deliver info faster Forrester Take Aways Denodo Enablers Fast data access; Information-as-a- service; Agile integration Organize canonical business entities used across dimensions Single View of Customer; Data distribution across channels Structured & unstructured; Internal & external; Real-time; Self-Service; Less replicated; Virtual Unified data abstraction layer democratizes access to single source of truth across and beyond organization boundaries Agile Data Architecture – How Denodo drives it
  • 42. © 2015 Denodo  Access any source  Make them look homogeneous  Pre-integrated graph of information for users  Build very rapidly  Data services feed many applications & users ROI? “..saved 1000s of development hours” “.. exceeded breakeven expectations – smash through it!” “.. tackled business value for more leverage, not IT cost” Agile Data Architecture – Capital Markets Firm
  • 43. © 2015 Denodo Agile Data Architecture – Technology Firm BI 2.0: Best of breed Complexity! Tamed by Data Virtualization
  • 44. © 2015 Denodo Data Virtualization - Two Approaches to Adopt Solve one/more projects Prove value Expand to other use cases Reusability and scalability Expand enterprise- wide Enterprise strategic vision Design for scale and support Systemic data services High value use cases first Multiple usage patterns Tactical Approach Enterprise-wide Approach People Process Technology Hybrid Approach Possible
  • 46. © 2015 Denodo Thank you! Data Virtualization for Business Intelligence and Business Agility in the Age of the Customer Four sessions providing insights and best practices for the Age of the Customer WEBINAR SERIES featuring FORRESTER RESEARCH