Organizations across most industries make some attempt to utilize Data Management and Data Strategies. While most organizations have both concepts implemented, they must fully understand the difference to fully achieve their goals.
This webinar will cover three lessons, each illustrated with examples, that will help you distinguish the difference between Data Strategy and Data Management processes and communicate their value to both internal and external decision-makers:
Understanding the difference between Data Strategy and Data Management
Prioritizing organizational Data Management needs vs. Data Strategy needs
Discuss foundational Data Management and Data Strategy concepts based on “The DAMA Guide to the Data Management Body of Knowledge” (DAMA DMBOK)
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Data Management vs Data Strategy
1. Peter Aiken, Ph.D.
Data Management
Versus
Data Strategy
Copyright 2018 by Data Blueprint Slide # !1
• DAMA International President 2009-2013
• DAMA International Achievement Award 2001 (with
Dr. E. F. "Ted" Codd
• DAMA International Community Award 2005
Peter Aiken, Ph.D.
• 33+ years in data management
• Repeated international recognition
• Founder, Data Blueprint (datablueprint.com)
• Associate Professor of IS (vcu.edu)
• DAMA International (dama.org)
• 10 books and dozens of articles
• Experienced w/ 500+ data
management practices
• 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.
The Case for the
Chief Data Officer
Recasting the C-Suite to Leverage
Your MostValuable Asset
Peter Aiken and
Michael Gorman
Copyright 2018 by Data Blueprint Slide #
2. • Context
– Important data properties
– Lack of correct educational focus
– Confusion: IT - Data - Business?
• Data Management
– What is it?
– Why is it important?
– State of the practice
– Functions required for effective data management
• Data Strategy
– Structural Approach
– Need for simplicity
– Foundational prerequisites
– The Theory of Constraints at work improving your data
• Take Aways/Q&A
– In Action In Concert
– Coordination is the necessary prerequisite
Data Governance Strategies
!3Copyright 2018 by Data Blueprint Slide #
Confusion
• IT thinks data is a business problem
– "If they can connect to the server, then my job is done!"
• The business thinks IT is managing data adequately
– "Who else would be taking care of it?"
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3. Separating the Wheat from the Chaff
• Better organized data increases in value
• Poor data management practices are costing
organizations much money/time/effort
• Minimally 80% of organizational data is ROT
– Redundant
– Obsolete
– Trivial
• The question is
– Which data to eliminate?
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Incomplete
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
!6Copyright 2018 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]
4. Executive Directive 7 (2016)
LEVERAGING THE USE OF SHARED DATAAND ANALYTICS
!7Copyright 2018 by Data Blueprint Slide #
Put simply, organizations:
!8Copyright 2018 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
5. Quality engineering/architecture work products do not happen accidentally!
• Data management happens 'pretty well' at
the workgroup level
– Defining characteristic of a workgroup
– Without guidance, what are the chances that all
workgroups are pulling toward the same objectives?
– Consider the time spent attempting informal practices
• Data chaff becomes sand
– Preventing smooth interoperation and exchanges
– Death by 1,000 cuts that have been difficult to account for
• Organizations and individuals lack
– Knowledge
– Skills
• Data Management (how)
• Data Strategy (why)
!9Copyright 2018 by Data Blueprint Slide #
• Context
– Important data properties
– Lack of correct educational focus
– Confusion: IT - Data - Business?
• Data Management
– What is it?
– Why is it important?
– State of the practice
– Functions required for effective data management
• Data Strategy
– Structural Approach
– Need for simplicity
– Foundational prerequisites
– The Theory of Constraints at work improving your data
• Take Aways/Q&A
– In Action In Concert
– Coordination is the necessary prerequisite
Data Governance Strategies
!10Copyright 2018 by Data Blueprint Slide #
6. 69 - datablueprint.com
Misunderstanding Data Management
!11Copyright 2018 by Data Blueprint Slide #
Data Management - Wikipedia Definition
Note: This is a broad definition
and encompasses professions
with no technical contact data
management technologies
such as database
management systems
"Data Resource Management is the development and execution of
architectures, policies, practices and procedures that properly manage
the full data lifecycle needs of an enterprise." http://dama.org
!12Copyright 2018 by Data Blueprint Slide #
7. The disks no longer rotate!
!13Copyright 2018 by Data Blueprint Slide #
database
architecture
engineering
effort
DataData
DataData
Data
Data
Data
Focus of a
software
architecture
engineering
effort Program A
Program B
Program C
Program F
Program E
Program D
Program G
Program H
Program I
Application
domain 1
Application
domain 2Application
domain 3
Data
Focus of a
Data
Data
Data Focus has Greater Potential Business Value
• Broader focus than
either software
architecture or
database
architecture
• Analysis scope is
on the system
wide use of data
• Problems caused
by data exchange
or interface
problems
• Architectural goals
more strategic
than operational
!14Copyright 2018 by Data Blueprint Slide #
8. Data Management Context
• Organization wide focus
• Requirement is to "understand"
• Understanding is of both current and future needs
• Making data effective and efficient
• Leverage data to support organizational activities
!15Copyright 2018 by Data Blueprint Slide #
Less ROT
Technologies
Process
People
Data Management
"Understanding the current
and future data needs of an
enterprise and making that
data effective and efficient
in supporting business
activities"
Aiken, P, Allen, M. D., Parker, B., Mattia, A., "Measuring Data Management's
Maturity: A Community's Self-Assessment" IEEE Computer (research feature
April 2007)
!16Copyright 2018 by Data Blueprint Slide #
9. What do we teach knowledge workers about data?
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What percentage of the deal with it daily?
What do we teach IT professionals about data?
!18Copyright 2018 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
12. • Context
– Important data properties
– Lack of correct educational focus
– Confusion: IT - Data - Business?
• Data Management
– What is it?
– Why is it important?
– State of the practice
– Functions required for effective data management
• Data Strategy
– Structural Approach
– Need for simplicity
– Foundational prerequisites
– The Theory of Constraints at work improving your data
• Take Aways/Q&A
– In Action In Concert
– Coordination is the necessary prerequisite
Data Governance Strategies
!23Copyright 2018 by Data Blueprint Slide #
Recent data "strategies"
• Data science
• Big data
• Analytics
• SAP
• Microsoft
• Google
• AWS
• ...
!24Copyright 2018 by Data Blueprint Slide #
undefinedtechnologies
13. Data Strategy in Context
!25Copyright 2018 by Data Blueprint Slide #
Organizational
Strategy
IT Strategy
Data Strategy
Organizational
Strategy
IT Strategy
Data Strategy
This is wrong!
!26Copyright 2018 by Data Blueprint Slide #
Organizational
Strategy
IT Strategy
Data Strategy
14. Organizational
Strategy
IT Strategy
This is correct …
!27Copyright 2018 by Data Blueprint Slide #
Data Strategy
Simon Sinek: How great leaders inspire action
!28Copyright 2018 by Data Blueprint Slide #
http://www.ted.com/talks/simon_sinek_how_great_leaders_inspire_action.html
What
How
Why
• “It’s not what you do,
it’s why you do it”
• Rev. Martin Luther King Jr.
gave the
- "I have a dream speech"
- not the
- "I have a plan speech"
15. What is a Strategy?
• Current use derived from military
• "a pattern in a stream of decisions" [Henry Mintzberg]
!29Copyright 2018 by Data Blueprint Slide #
Strategy in Action: Napoleon defeats a larger enemy
• Question?
– How to I defeat the competition when their forces
are bigger than mine?
• Answer:
– Divide
and
conquer!
– “a pattern
in a stream
of decisions”
!30Copyright 2018 by Data Blueprint Slide #
– “a pattern
in a stream
of decisions”
16. !31Copyright 2018 by Data Blueprint Slide #
Supply Line Metadata
First Divide
!32Copyright 2018 by Data Blueprint Slide #
17. !33Copyright 2018 by Data Blueprint Slide #
Then Conquer
Wayne Gretzky’s
Definition of Strategy
He skates to where he
thinks the puck will be ...
!34Copyright 2018 by Data Blueprint Slide #
18. Former Walmart Business Strategy
!35Copyright 2018 by Data Blueprint Slide #
Every
Day Low
Price
V1
Organizations
without
a formalized
data strategy
V3
Data Strategy: Use data
to create strategic
opportunities
V4
Data Strategy: both
Improve Operations
Innovation
The focus of data strategy should be sequenced
!36Copyright 2018 by Data Blueprint Slide #
Only 1 is 10 organizations has a board
approved data strategy!
V2
Data Strategy: Increase
organizational efficiencies/
effectiveness
X
X
19. Strategy
!37Copyright 2018 by Data Blueprint Slide #
A pattern
in a stream
of decisions
Data programmes preceding software projects
!38Copyright 2018 by Data Blueprint Slide #
Common Organizational Data
(and corresponding data needs requirements)
New Organizational
Capabilities
Systems
Development
Activities
Create
Evolve
Future State
(Version +1)
Data evolution is separate from,
external to, and precedes system
development life cycle activities!
Data is not a project!
20. !39Copyright 2018 by Data Blueprint Slide #
• Before further construction could proceed
• No IT equivalent
Our barn had to pass a foundation inspection
You can accomplish
Advanced Data Practices
without becoming proficient
in the Foundational Data
Practices however
this will:
• Take longer
• Cost more
• Deliver less
• Present
greater
risk (with thanks to
Tom DeMarco)
Data Management Practices Hierarchy
Advanced
Data
Practices
• MDM
• Mining
• Big Data
• Analytics
• Warehousing
• SOA
Foundational Data Practices
Data Platform/Architecture
Data Governance Data Quality
Data Operations
Data Management Strategy
Technologies
Capabilities
!40Copyright 2018 by Data Blueprint Slide #
21. DMM℠ Structure of
5 Integrated
DM Practice Areas
Data architecture
implementation
Data
Governance
Data
Management
Strategy
Data
Operations
Platform
Architecture
Supporting
Processes
Maintain fit-for-purpose data,
efficiently and effectively
!41Copyright 2018 by Data Blueprint Slide #
Manage data coherently
Manage data assets professionally
Data life cycle
management
Organizational support
Data
Quality
Data Management
Strategy is often the
weakest link
Data architecture
implementation
Data
Governance
Data
Management
Strategy
Data
Operations
Platform
Architecture
Supporting
Processes
Maintain fit-for-purpose data,
efficiently and effectively
!42Copyright 2018 by Data Blueprint Slide #
Manage data coherently
Manage data assets professionally
Data life cycle
management
Organizational support
Data
Quality
3 3
33
1
22. • A management paradigm that views any
manageable system as being limited in
achieving more of its goals by a small
number of constraints
• 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
!43Copyright 2018 by Data Blueprint Slide #
https://en.wikipedia.org/wiki/Theory_of_constraints
(TOC)
Theory of Constraints
!44Copyright 2018 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
23. Theory of Constraints at work
improving your data
!45Copyright 2018 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
• Context
– Important data properties
– Lack of correct educational focus
– Confusion: IT - Data - Business?
• Data Management
– What is it?
– Why is it important?
– State of the practice
– Functions required for effective data management
• Data Strategy
– Structural Approach
– Need for simplicity
– Foundational prerequisites
– The Theory of Constraints at work improving your data
• Take Aways/Q&A
– In Action In Concert
– Coordination is the necessary prerequisite
Data Governance Strategies
!46Copyright 2018 by Data Blueprint Slide #
24. Bad Data Decisions Spiral
!47Copyright 2018 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
!48Copyright 2018 by Data Blueprint Slide #
Organizational
Strategy
Data Strategy
IT Projects
Organizational Operations
Data
Management
Data Strategy in Context
Data
asset support for
organizational
strategy
What the data
assets need to do to
support strategy
How well data is
supporting strategy
Operational
feedback
How IT
supports strategy
Other
aspects of
organizational
strategy
25. Take Aways
!49Copyright 2018 by Data Blueprint Slide #
• This discipline has not had 8,000 years
to formalize practices ➡ GAAP
• Your data is a mess and requires professional
ministration to make up for past neglect
• Your folks don't know how to use or improve it effectively
• You likely require a new business data program
• Data strategy and data management are major data
program components, in concert, they must focus on
1. Improving organizational data
2. Improving the way people use data
3. Improving how people use better data to support strategy
This can only be accomplished incrementally using an
iterative, approach focusing on one aspect at a time
and applying formal transformation methods
data program!business
Data Governance Strategies
• Context
– Important data properties
– Lack of correct educational focus
– Confusion: IT - Data - Business?
• Data Management
– What is it?
– Why is it important?
– State of the practice
– Functions required for effective data management
• Data Strategy
– Structural Approach
– Need for simplicity
– Foundational prerequisites
– The Theory of Constraints at work improving your data
• Take Aways/Q&A
– In Action In Concert
– Coordination is the necessary prerequisite
!50Copyright 2018 by Data Blueprint Slide #
26. Questions?
!51Copyright 2018 by Data Blueprint Slide #
It’s your turn!
Use the chat feature to submit
your questions to Peter now.
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August Webinar:
Getting Started with Data Stewardship
August 14, 2018 @ 2:00 PM ET
September Webinar:
Metadata Strategies
September 11, 2018 @ 2:00 PM ET
October Webinar:
Data Quality
October 9, 2018 @ 2:00 PM ET
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