Your Data Strategy should be concise, actionable, and understandable by business and IT! Data is not just another resource. It is your most powerful, yet poorly managed and therefore underutilized organizational asset. Data are your sole non-depletable, non-degradable, durable strategic assets, and they are pervasively shared across every organizational area. Overcoming lack of talent, barriers in organizational thinking, and seven specific data sins are organizational prerequisites to be satisfied before (a measurable) nine out of 10 organizations can achieve the three primary goals of an organizational Data Strategy, which are to: - Improve the way your people use data - Improve the way your people use data to achieve your organizational strategy - Improve your organization’s data In this manner, your organizational Data Strategy can be used to best focus your data assets in precise support of your organization's strategic objectives. Once past the prerequisites, organizations must develop a disciplined, repeatable means of improving the data literacy, standards, and supply as business objectives in specific areas that become the foci of subsequent Data Governance efforts. This process (based on the theory of constraints) is where the strategic data work really occurs, as organizations identify prioritized areas where better assets, literacy, and support (Data Strategy components) can help an organization better achieve specific strategic objectives. Then the process becomes lather, rinse, and repeat. Several complementary concepts are covered, including: - A cohesive argument for why Data Strategy is necessary for effective Data Governance - An overview of prerequisites for effective Data Strategy, as well as common pitfalls that can detract from its implementation, such as the “Seven Deadly Data Sins” - A repeatable process for identifying and removing data constraints, and the importance of balancing business operation and innovation while doing so

1. Data Strategy Best Practices
Your data strategy should be concise, actionable, and understandable by business and IT!
Copyright 2019 by Data Blueprint Slide # !1
Peter Aiken, Ph.D.
• DAMA International President 2009-2013 / 2018
• DAMA International Achievement Award 2001
(with Dr. E. F. "Ted" Codd
• DAMA International Community Award 2005
Copyright 2019 by Data Blueprint Slide # !2
Peter Aiken, Ph.D.
• I've been doing this a long time
• My work is recognized as useful
• Associate Professor of IS (vcu.edu)
• Founder, Data Blueprint (datablueprint.com)
• DAMA International (dama.org)
• 10 books and dozens of articles
• Experienced w/ 500+ data
management practices worldwide
• Multi-year immersions
– US DoD (DISA/Army/Marines/DLA)
– Nokia
– Deutsche Bank
– Wells Fargo
– Walmart
– …
PETER AIKEN WITH JUANITA BILLINGS
FOREWORD BY JOHN BOTTEGA
MONETIZING
DATA MANAGEMENT
Unlocking the Value in Your Organization’s
Most Important Asset.

2. 1Infogix Confidential Copyright 2018Infogix Confidential Copyright 2018
Dataversity
Data Strategy Best Practices
January 8, 2019

3. 2Infogix Confidential Copyright 2018
Matt Guschwan, Ph.D.
• Data Strategy Consultant
Intro

4. 3Infogix Confidential Copyright 2018
• Portfolio Approach
• Central Office of Data
• Startup and scale
• Investments into People, Process & Technology
• Data connects P, P & T
ROI Mandate
D a t a S t r a t e g y B e s t P r a c t i c e s

5. 4Infogix Confidential Copyright 2018Infogix Confidential Copyright 2018
Enjoy the Presentation!
Contact: Matt Guschwan mguschwan@infogix.com

6. Best Practices
!3Copyright 2019 by Data Blueprint Slide #
A best practice is a method or technique
that has been generally accepted as
superior to any alternatives because it:
1. produces results that are superior to
those achieved by other means or
2. because it has become a standard way
of doing things,
e.g., a standard way of complying with legal
or ethical requirements.
!4Copyright 2019 by Data Blueprint Slide #
• A data strategy specifies how data assets are to be used to
support the organizational strategy
– What is strategy?
– What is a data strategy?
– How do they work together?
• A data strategy is necessary for effective data governance
– Improve your organization’s data
– Improve the way people use their data
– Improving how people use data to support their organizational strategy
• Effective Data Strategy Prerequisites
– Lack of organizational readiness
– Failure to compensate for the lack of data competencies
– Eliminating the barriers to leveraging data,
the seven deadly data sins
• Data Strategy Development Phase II–Iterations
– Lather, rinse, repeat
– A balanced approach is required
• Q&A
Data Strategy Best Practices

7. What is a Strategy?
!5Copyright 2019 by Data Blueprint Slide #
• Current use derived from military
• “a pattern in a stream of decisions” [Henry Mintzberg]
Former Walmart Business Strategy
!6Copyright 2019 by Data Blueprint Slide #
Every
Day Low
Price

8. Wayne Gretzky’s
Definition of Strategy
!7Copyright 2019 by Data Blueprint Slide #
He skates to where he
thinks the puck will be ...
Strategy in Action: Napoleon defeats a larger enemy
• Question?
– How do I defeat the competition when their forces
are bigger than mine?
• Answer:
– Divide
and
conquer!
– “a pattern
in a stream
of decisions”
!8Copyright 2019 by Data Blueprint Slide #

9. !9Copyright 2019 by Data Blueprint Slide #
SupplyLineMetadata
(aspartofadivideandconquerstrategy)
First Divide
!10Copyright 2019 by Data Blueprint Slide #

10. Then Conquer
!11Copyright 2019 by Data Blueprint Slide #
Complex Strategy
• First
– Hit both armies
hard at just the
right spot
• Then
– Turn right and
defeat the
Prussians
• Then
– Turn left and
defeat the
British
!12Copyright 2019 by Data Blueprint Slide #
W
hile someone else is
shooting at you!

11. !13Copyright 2019 by Data Blueprint Slide #
• The highest level data
guidance available to an
organization, ...
• ... focusing data-related
activities on articulated data
goal achievements and ...
• ... providing directional but
specific guidance when
faced with a stream of
decisions or uncertainties
about organizational data
assets and their application
toward business objectives
Your Data Strategy
Strategy that winds up only on a shelf is not useful
!14Copyright 2019 by Data Blueprint Slide #
Data
Strategy

12. Strategy provides context for the guidance
!15Copyright 2019 by Data Blueprint Slide #
Managing
Data with
Guidance
Managing Data with Guidance
• How should data be used and in which business
processes?
• How is data shared among users, divisions, geographies
and partners?
• What processes and
procedures allow for
data to be changed?
• Who manages
approval processes?
• What processes
ensure compliance?
• Most importantly, in
what order should I
approach the above list?
!16Copyright 2019 by Data Blueprint Slide #

13. !17Copyright 2019 by Data Blueprint Slide #
Organizational
Strategy
Data Strategy
IT Projects
Organizational Operations
Data
Governance
Data Strategy and Data Governance in Context
Data
asset support for
organizational
strategy
What the
data assets do to
support strategy
How well the data
strategy is working
Operational
feedback
How data is
delivered by IT
How IT
supports strategy
Other
aspects of
organizational
strategy
Data Strategy in Context
!18Copyright 2019 by Data Blueprint Slide #
Organizational
Strategy
IT Strategy
Data Strategy

14. Organizational
Strategy
IT Strategy
Data Strategy
This is wrong!
!19Copyright 2019 by Data Blueprint Slide #
Organizational
Strategy
IT Strategy
Data Strategy
Organizational
Strategy
IT Strategy
This is correct …
!20Copyright 2019 by Data Blueprint Slide #
Data Strategy

15. Strategy provides context for the guidance
!15Copyright 2019 by Data Blueprint Slide #
Managing
Data with
Guidance
Managing Data with Guidance
• How should data be used and in which business
processes?
• How is data shared among users, divisions, geographies
and partners?
• What processes and
procedures allow for
data to be changed?
• Who manages
approval processes?
• What processes
ensure compliance?
• Most importantly, in
what order should I
approach the above list?
!16Copyright 2019 by Data Blueprint Slide #

16. Organizational Assets
• Cash & other financial instruments
• Real property
• Inventory
• Intellectual Property
• Human
– Knowledge
– Skills
– Abilities
• Financial
• Organizational reputation
• Good will
• Brand name
• Data!!!
!23Copyright 2019 by Data Blueprint Slide #
Separating the Wheat from the Chaff
• Data that is better organized increases
in value
• Poor data management practices are costing
organizations money/time/effort
• 80% of organizational data is ROT
– Redundant
– Obsolete
– Trivial
!24Copyright 2019 by Data Blueprint Slide #
Incomplete

17. Data Assets Win!
Data
Assets
Financial
Assets
Real
Estate Assets
Inventory
Assets
Non-
depletable
Available for
subsequent
use
Can be
used up
Can be
used up
Non-
degrading √ √ Can degrade
over time
Can degrade
over time
Durable Non-taxed √ √
Strategic
Asset √ √ √ √
Data Assets Win!
• Today, data is the most powerful, yet underutilized and poorly
managed organizational asset
• Data is your
– Sole
– Non-depletable
– Non-degrading
– Durable
– Strategic
• Asset
– Data is the new oil!
– Data is the new (s)oil!
– Data is the new bacon!
• As such, data deserves:
– It's own strategy
– Attention on par with similar organizational assets
– Professional ministration to make up for past neglect
!25Copyright 2019 by Data Blueprint Slide #
Asset: A resource controlled by the organization as a result of past events or
transactions and from which future economic benefits are expected to flow [Wikipedia]
!26Copyright 2019 by Data Blueprint Slide #
Organizational
Strategy
Data Strategy
IT Projects
Organizational Operations
Data
Governance
Data Strategy and Data Governance in Context
Data
asset support for
organizational
strategy
What the
data assets do to
support strategy
How well the data
strategy is working
Operational
feedback
How data is
delivered by IT
How IT
supports strategy
Other
aspects of
organizational
strategy

18. !27Copyright 2019 by Data Blueprint Slide #
Data Strategy
Data
Governance
Data Strategy & Data Governance
What the data
assets do to support
strategy
How well the data
strategy is working
(Business Goals)
(Metadata)
Reasons for a Data Strategy
!28Copyright 2019 by Data Blueprint Slide #
Improve your
organization’s data
Improve the way your
people use its data
Improve the way your
data and your people
support your
organizational strategy
• Because data
points to where
valuable things
are located
• Because data has
intrinsic value by
itself
• Because data
has inherent
combinatorial
value
• Valuing Data
– Use data to
measure change
– Use data to
manage change
– Use data to
motivate change
• Creating a
competitive
advantage with
data

19. • Old model
– Sell jet engines
• New model
– Sell hours of thrust power
– Power-by-the-hour
– No payment for down time
– Wing to wing
– When was it invented?
What did Rolls Royce Learn
!29Copyright 2019 by Data Blueprint Slide #
from Nascar?
!30Copyright 2019 by Data Blueprint Slide #
• A data strategy specifies how data assets are to be used to
support the organizational strategy
– What is strategy?
– What is a data strategy?
– How do they work together?
• A data strategy is necessary for effective data governance
– Improve your organization’s data
– Improve the way people use their data
– Improving how people use data to support their organizational strategy
• Effective Data Strategy Prerequisites
– Lack of organizational readiness
– Failure to compensate for the lack of data competencies
– Eliminating the barriers to leveraging data,
the seven deadly data sins
• Data Strategy Development Phase II–Iterations
– Lather, rinse, repeat
– A balanced approach is required
• Q&A
Data Strategy Best Practices

20. !31Copyright 2019 by Data Blueprint Slide #
Data Strategy
Data Strategy is Implemented in 2 Phases
What the
data assets do to
support strategy
Phase I-Prerequisites
1) Prepare for dramatic change and determine how to do the work
2) Recruit a qualified, knowledgeable enterprise data executive (and
other qualified talent)
3) Eliminate the Seven Deadly Data Sins
Phase II-Iterations (Lather, Rinse, Repeat)
!32Copyright 2019 by Data Blueprint Slide #
Data Strategy
Data Strategy is Implemented in 2 Phases
What the
data assets do to
support strategy
Phase I-Prerequisites
1) Prepare for dramatic change and determine how to do the work
2) Recruit a qualified, knowledgeable enterprise data executive (and
other qualified talent)
3) Eliminate the Seven Deadly Data Sins
Phase II-Iterations (Lather, Rinse, Repeat)

21. !33Copyright 2017 by Data Blueprint Slide #
CIOs
aren't
!34Copyright 2019 by Data Blueprint Slide #
Credit: Image credit: Matt Vickers

22. Change the status quo!
• Keep in mind that the appointment of a
CDO typically comes from a high-level
decision. In practice, it can trigger an array
of problematic reactions within the
organization including:
– Confusion,
– Uncertainty,
– Doubt,
– Resentment and
– Resistance.
• CDOs need to rise to the challenge of
changing the status quo if they expect to
lead the business in making data a
strategic asset.
– from What Chief Data Officers Need to Do to
Succeed by Mario Faria
!35Copyright 2019 by Data Blueprint Slide #
Change Management & Leadership
!36Copyright 2019 by Data Blueprint Slide #

23. Diagnosing Organizational Readiness
!37Copyright 2019 by Data Blueprint Slide #
adapted from the Managing Complex Change model by Dr. Mary Lippitt, 1987
Culture is the biggest impediment to a
shift in organizational thinking about data!
QR Code for PeterStudy
• Free Case Study Download• Free Case Study Download
– http://dl.acm.org/citation.cfm?doid=2888577.2893482
or
http://tinyurl.com/PeterStudy
or scan the QR Code at the right
!38Copyright 2019 by Data Blueprint Slide #

24. !31Copyright 2019 by Data Blueprint Slide #
Data Strategy
Data Strategy is Implemented in 2 Phases
What the
data assets do to
support strategy
Phase I-Prerequisites
1) Prepare for dramatic change and determine how to do the work
2) Recruit a qualified, knowledgeable enterprise data executive (and
other qualified talent)
3) Eliminate the Seven Deadly Data Sins
Phase II-Iterations (Lather, Rinse, Repeat)
!32Copyright 2019 by Data Blueprint Slide #
Data Strategy
Data Strategy is Implemented in 2 Phases
What the
data assets do to
support strategy
Phase I-Prerequisites
1) Prepare for dramatic change and determine how to do the work
2) Recruit a qualified, knowledgeable enterprise data executive (and
other qualified talent)
3) Eliminate the Seven Deadly Data Sins
Phase II-Iterations (Lather, Rinse, Repeat)

25. What do we teach knowledge workers about data?
!41Copyright 2019 by Data Blueprint Slide #
What percentage of the deal with it daily?
What do we teach IT professionals about data?
!42Copyright 2019 by Data Blueprint Slide #
• 1 course
– How to build a
new database
• What
impressions do IT
professionals get
from this
education?
– Data is a technical
skill that is needed
when developing
new databases
• If we are migrating databases, we are not creating new
databases and we don't need organizational data
management knowledge, skills, and abilities (KSAs).
• If we are implementing a new software package, we are
not creating a new database and therefore we do not
need data management KSAs.
• If we are installing an enterprise resource package
(ERP), we are not creating a new database and therefore
we do not need data management KSAs.

26. Put simply, organizations:
!43Copyright 2019 by Data Blueprint Slide #
• Have little idea what data they have
• Do not know where it is (and)
• Do not know what their knowledge workers do with it
Bad Data Decisions Spiral
!44Copyright 2019 by Data Blueprint Slide #
Bad data decisions
Technical deci-
sion makers are not
data knowledgable
Business decision
makers are not
data knowledgable
Poor organizational outcomes
Poor treatment of
organizational data
assets
Poor
quality
data

27. Hiring Panels Are Often
Not Qualified to Help
!45Copyright 2019 by Data Blueprint Slide #
The Enterprise Data Executive Takes One for the Team
!46Copyright 2019 by Data Blueprint Slide #

28. !47Copyright 2019 by Data Blueprint Slide #
Data Strategy
Data Strategy is Implemented in 2 Phases
What the
data assets do to
support strategy
Phase I-Prerequisites
1) Prepare for dramatic change and determine how to do the work
2) Recruit a qualified, knowledgeable enterprise data executive (and
other qualified talent)
3) Eliminate the Seven Deadly Data Sins
Phase II-Iterations (Lather, Rinse, Repeat)
!48Copyright 2019 by Data Blueprint Slide #

29. Not Understanding Data-Centric Thinking
Lacking Qualified Data Leadership
Not implementing a Robust, Programmatic Means of
Developing Shared Data
Not Aligning The Data Program with IT Projects
Failing to Adequately Manage Expectations
Not Sequencing Data
Strategy Implementation
Failing To Address
Cultural And Change
Management Challenges
Not Understanding Data-Centric Thinking
Lacking Qualified Data Leadership
Not implementing a Robust, Programmatic Means of
Developing Shared Data
Not Aligning The Data Program with IT Projects
Failing to Adequately Manage Expectations
Not Sequencing Data
Strategy Implementation
Failing To Address
Cultural And Change
Management Challenges
Not Understanding Data-Centric Thinking
Lacking Qualified Data Leadership
Not implementing a Robust, Programmatic Means of
Developing Shared Data
Not Aligning The Data Program with IT Projects
Failing to Adequately Manage Expectations
Not Sequencing Data
Strategy Implementation
Failing To Address
Cultural And Change
Management Challenges
Not Understanding Data-Centric Thinking
Lacking Qualified Data Leadership
Not implementing a Robust, Programmatic Means of
Developing Shared Data
Not Aligning The Data Program with IT Projects
Failing to Adequately Manage Expectations
Not Sequencing Data
Strategy Implementation
Failing To Address
Cultural And Change
Management Challenges
Not Understanding Data-Centric Thinking
Lacking Qualified Data Leadership
Not implementing a Robust, Programmatic Means of
Developing Shared Data
Not Aligning The Data Program with IT Projects
Failing to Adequately Manage Expectations
Not Sequencing Data
Strategy Implementation
Failing To Address
Cultural And Change
Management Challenges
Not Understanding Data-Centric Thinking
Lacking Qualified Data Leadership
Not implementing a Robust, Programmatic Means of
Developing Shared Data
Not Aligning The Data Program with IT Projects
Failing to Adequately Manage Expectations
Not Sequencing Data
Strategy Implementation
Failing To Address
Cultural And Change
Management Challenges
Not Understanding Data-Centric Thinking
Lacking Qualified Data Leadership
Not implementing a Robust, Programmatic Means of
Developing Shared Data
Not Aligning The Data Program with IT Projects
Failing to Adequately Manage Expectations
Not Sequencing Data
Strategy Implementation
Failing To Address
Cultural And Change
Management Challenges
!49Copyright 2019 by Data Blueprint Slide #
Exorcising the Seven Deadly Data Sins
g Data-
ng
Lacking Qualified Data
Leadership
Failing to Implement a
Programmatic Way to
Share Data
Not Aligning the Data
Program with IT Projects
ailing to Adequately
anage Expectations
Not Sequencing Data
Strategy Implementation
Not Addressing Cultural
and Change
Management Challenges
2 3 4
5 6 7
Not Understanding Data-
Centric Thinking
Lacking Qualified Data
Leadership
Failing to Implement a
Programmatic Way to
Share Data
Not Aligning the Data
Program with IT Projects
Failing to Adequately
Manage Expectations
Not Sequencing Data
Strategy Implementation
Not Addressing Cultural
and Change
Management Challenges
1 2 3 4
5 6 7
Not Understanding Data-
Centric Thinking
Lacking Qualified Data
Leadership
Failing to Implement a
Programmatic Way to
Share Data
Not Aligning the Data
Program with IT Projects
Failing to Adequately
Manage Expectations
Not Sequencing Data
Strategy Implementation
Not Addressing Cultural
and Change
Management Challenges
1 2 3 4
5 6 7t Understanding Data-
Centric Thinking
Lacking Qualified Data
Leadership
Failing to Implement a
Programmatic Way to
Share Data
Not Aligning the Data
Program with IT Projects
Failing to Adequately
Manage Expectations
Not Sequencing Data
Strategy Implementation
Not Addressing Cultural
and Change
Management Challenges
1 2 3 4
5 6 7
acking Qualified Data
Leadership
Failing to Implement a
Programmatic Way to
Share Data
Not Aligning the Data
Program with IT Projects
ately
tions
Not Sequencing Data
Strategy Implementation
Not Addressing Cultural
and Change
Management Challenges
2 3 4
6 7
Not Understanding Data-
Centric Thinking
Lacking Qualified Data
Leadership
Failing to Implement a
Programmatic Way to
Share Data
Not Aligning the Data
Program with IT Projects
Failing to Adequately
Manage Expectations
Not Sequencing Data
Strategy Implementation
Not Addressing Cultural
and Change
Management Challenges
1 2 3 4
5 6 7
Not Understanding Data-
Centric Thinking
Lacking Qualified Data
Leadership
Failing to Implement a
Programmatic Way to
Share Data
Not Aligning the Data
Program with IT Projects
Failing to Adequately
Manage Expectations
Not Sequencing Data
Strategy Implementation
Not Addressing Cultural
and Change
Management Challenges
1 2 3 4
5 6 7
Introducing The Data Doctrine
Copyright 2019 by Data Blueprint Slide #
!50
http://www.thedatadoctrine.com

30. !51Copyright 2019 by Data Blueprint Slide #
• A data strategy specifies how data assets are to be used to
support the organizational strategy
– What is strategy?
– What is a data strategy?
– How do they work together?
• A data strategy is necessary for effective data governance
– Improve your organization’s data
– Improve the way people use their data
– Improving how people use data to support their organizational strategy
• Effective Data Strategy Prerequisites
– Lack of organizational readiness
– Failure to compensate for the lack of data competencies
– Eliminating the barriers to leveraging data,
the seven deadly data sins
• Data Strategy Development Phase II–Iterations
– Lather, rinse, repeat
– A balanced approach is required
• Q&A
Data Strategy Best Practices
!52Copyright 2019 by Data Blueprint Slide #
• A data strategy specifies how data assets are to be used to
support the organizational strategy
– What is strategy?
– What is a data strategy?
– How do they work together?
• A data strategy is necessary for effective data governance
– Improve your organization’s data
– Improve the way people use their data
– Improving how people use data to support their organizational strategy
• Effective Data Strategy Prerequisites
– Lack of organizational readiness
– Failure to compensate for the lack of data competencies
– Eliminating the barriers to leveraging data,
the seven deadly data sins
• Data Strategy Development Phase II–Iterations
– Lather, rinse, repeat
– A balanced approach is required
• Q&A
Data Strategy Best Practices

31. !53Copyright 2019 by Data Blueprint Slide #
Data Strategy
Data Strategy is Implemented in 2 Phases
Phase I-Prerequisites
1) Prepare for dramatic change and determined how to do the work
2) Recruit a qualified, knowledgeable enterprise data executive
(and other qualified talent)
3) Eliminate the Seven Deadly Data Sins
Phase II-Iterations (Lather, Rinse, Repeat)
You
are
here
1) Identify the primary constraint keeping data from fully supporting strategy
2) Exploit organizational efforts to remove this constraint
3) Subordinate everything else to this exploitation decision
4) Elevate the data constraint
5) Repeat the above steps to address the new constraint
!54Copyright 2019 by Data Blueprint Slide #
The Goal

32. • A management paradigm that views any
manageable system as being limited in
achieving more of its goals by a small
number of constraints(Eliyahu M. Goldratt)
• There is always at least one constraint, and
TOC uses a focusing process to identify the constraint and
restructure the rest of the organization to address it
• TOC adopts the common idiom "a
chain is no stronger than its
weakest link," processes,
organizations, etc., are vulnerable
because the weakest component
can damage or break them or at
least adversely affect the outcome
!55Copyright 2019 by Data Blueprint Slide #
https://en.wikipedia.org/wiki/Theory_of_constraints
(TOC)
Theory of Constraints - Generic
!56Copyright 2019 by Data Blueprint Slide #
Identify the current constraints,
the components of the system
limiting goal realization
Make quick
improvements
to the constraint
using existing
resources
Review other activities in the process facilitate proper alignment and support of constraint
If the constraint
persists, identify other
actions to eliminate
the constraint
Repeat until the
constraint is
eliminated
Alleviate

33. Theory of Constraints at work
improving your data
!57Copyright 2019 by Data Blueprint Slide #
In your analysis of how
organization data can best
support organizational strategy
one thing is blocking you most -
identify it!
Try to fix it
rapidly with out
restructuring
(correct it
operationally)
Improve existing data evolution activities to ensure singular focus on the current objective
Restructure to
address constraint
Repeat until data
better supports
strategy
Alleviate
Data Strategy Framework (Part 2)
!58Copyright 2019 by Data Blueprint Slide #
• Benefits & Success Criteria
• Capability Targets
• Solution Architecture
• Organizational Development
Solution
• Leadership & Planning
• Project Dev. & Execution
• Cultural Readiness
Road Map
• Organization Mission
• Strategy & Objectives
• Organizational Structures
• Performance Measures
Business Needs
• Organizational / Readiness
• Business Processes
• Data Management Practices
• Data Assets
• Technology Assets
Current State
• Business Value Targets
• Capability Targets
• Tactics
• Data Strategy Vision
Strategic Data Imperatives
Business
Needs
Existing
Capabilities
ExecutionBusiness
Value
New
Capabilities

34. Upcoming Events
January NYC Visit:
Your Data Strategy
January 17, 2019 @ 9:00 AM ET
https://damany.starchapter.com/meet-reg1.php?id=102 (free for members $20 non-members)
February Webinar:
Data Architecture versus Data Modeling
February 12, 2019 @ 2:00 PM ET
March Webinar:
Reference & Master Data Management - Unlocking Business Value
March 12, 2019 @ 2:00 PM ET
Enterprise Data World
How I Learned to Stop Worrying & Love My Data Warehouse
Sunday, 3/17/2019 @ 1:30 PM ET
Data Management Brain Drain
Thursday, 3/21/2019 @ 8:30 AM ET
Sign up for webinars at:
www.datablueprint.com/webinar-schedule or www.dataversity.net
!59Copyright 2019 by Data Blueprint Slide #
Brought to you by:
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+ =
!60Copyright 2019 by Data Blueprint Slide #
It’s your turn!
Use the chat
feature or Twitter
(#dataed) to submit
your questions now!

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804.521.4056
Copyright 2019 by Data Blueprint Slide # !61