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Peter Aiken, PhD
Exorcising
the Seven Deadly Data Sins
!1
• DAMA International President 2009-2013 / 2018
• DAMA International Achievement Award 2001 

(with Dr. E. F. "Ted" Codd
• DAMA International Community Award 2005
Copyright 2018 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.
George Box

British Statistician
(1919-2013)
“All models are wrong, ...
... some are useful.”
!3Copyright 2018 by Data Blueprint Slide #
!4Copyright 2018 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
Link to amazon.com
IT Project Failure Rates (1994-2015)
Source: Standish Chaos Reports as reported at: http://standishgroup.com
!5Copyright 2018 by Data Blueprint Slide #
0%
15%
30%
45%
60%
1994 1996 1998 2000 2002 2004 2006 2008 2010 2011 2012 2013 2014 2015
Failed Challenged Succeeded
System
HardwareProcessesPeople Software
• A set of detailed methods, procedures, and routines established or
formulated to carry out a specific activity, perform a duty, or solve a
problem.
• An organized, purposeful structure regarded as a whole and consisting
of interrelated and interdependent elements (components, entities,
factors, members, parts, etc.). These elements continually influence one
another (directly or indirectly) to maintain their activity and the existence
of the system, in order to achieve the goal of the system. 

http://www.businessdictionary.com/definition/system.html#ixzz23T7LyAjJ
System
!6Copyright 2018 by Data Blueprint Slide #
DataData
How much data,

by the minute!
For the entirety of 2017,
every minute of every day:
• (almost) Seventy
thousand hours of Netflix
• (almost) a half million
tweets
• 15+ million texts
• 3.5+ million google
searches
• 103+ million email
spams
!7Copyright 2018 by Data Blueprint Slide #
https://www.domo.com/learn/data-never-sleeps-5
There will
never be less
data than
right now!
!8Copyright 2018 by Data Blueprint Slide #
As articulated by Micheline Casey
!9Copyright 2018 by Data Blueprint Slide #
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
!10Copyright 2017 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
Diagnosing Organizational Readiness
!11Copyright 2018 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!
!12Copyright 2018 by Data Blueprint Slide #
Credit: Image credit: Matt Vickers
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
!13Copyright 2018 by Data Blueprint Slide #
Change Management & Leadership
!14Copyright 2018 by Data Blueprint Slide #
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
!15Copyright 2018 by Data Blueprint Slide #
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
!16Copyright 2017 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
The DAMA Guide
to the Data
Management 

Body of 

Knowledge
!17Copyright 2018 by Data Blueprint Slide #
Data 

Management
Functions
fromTheDAMAGuidetotheDataManagementBodyofKnowledge©2009byDAMAInternational
• Good enough 

to criticize
– All models 

are wrong
– Some models 

are useful
• Missing two 

important concepts
– Optionality
– Dependency
Our barn had to pass a foundation inspection
• Before further construction could proceed
• No IT equivalent
!18Copyright 2018 by Data Blueprint Slide #
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
!19Copyright 2018 by Data Blueprint Slide #


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
!20Copyright 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
Sequencing the Reasons for a Data Strategy
!21Copyright 2018 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
What did Rolls Royce Learn
• 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?
!22Copyright 2018 by Data Blueprint Slide #
from Nascar?
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
!23Copyright 2017 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 7
Data Implementation Framework
!24Copyright 2018 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
Data Management Program Expenses
• 5 Data Managers
– Each paid $100,000/year
– Do they feel obligated to demonstrate $500,000 in
benefits annually?
• When will you be done?
– "It's okay my CIO gave me 5 years!"
– Revised benefits goal is $2.5 million
Copyright 2018 by Data Blueprint Slide #
!25
improving how the state prices and sells its goods and services, and more efficiently matching
citizens to benefits when they enroll.
“The first year of our data internship partnership has been a success,” said Governor McAuliffe.
“The program has helped the state save time and money by making some of our internal
processes more efficient and modern. And it has given students valuable real-world experience. I
look forward to seeing what the second year of the program can accomplish.”
“Data is an important resource that becomes even more critical as technology progresses,” said
VCU President Michael Rao, Ph.D. “VCU is uniquely positioned, both in its location and
through the wealth of talent at the School of Business, to help state agencies run their data-
centric systems more efficiently, while giving our students hands-on practice in the development
of data systems.”
During their internships, pairs of VCU students work closely with state agency CIOs to identify
specific business cases in which data can be used. Participants gain practical experience in using
data to drive re-engineering, while participating CIOs have concrete examples of how to make
better use of data to provide innovative and less costly services to citizens.
"Working with the talented VCU students gave us a different perspective on what the data was
telling us,” said Dave Burhop, Deputy Commissioner/CIO of the Virginia Department of Motor
Vehicles.
“The VCU interns provided an invaluable resource to the Governor’s Coordinating Council on
Homelessness,” said Pamela Kestner, Special Advisor on Families, Children and Poverty.
“They very effectively reviewed the data assets available in the participating state agencies and
identified analytic content that can be used to better serve the homeless population.”
“It's always useful to have ‘fresh eyes’ on data that we are used to seeing,” said Jim Rothrock,
Commissioner of the Department for Aging and Rehabilitative Services. “Our interns challenged
us and the way we interpret data. It was a refreshing and useful, and we cannot wait for new
experiences with new students.”
The data internships support Governor McAuliffe’s ongoing initiative to provide easier access to
open data in Virginia. The internships also support treating data as an enterprise asset, one of
four strategic goals of the enterprise information architecture strategy adopted by the
Commonwealth in August 2013. Better use of data allows the Commonwealth to identify
opportunities to avoid duplicative costs in collecting, maintaining and using information; and to
integrate services across agencies and localities to improve responses to constituent needs and
optimize government resources.
Virginia Secretary of Technology Karen Jackson and CIO of the Commonwealth Nelson Moe
are leading the effort on behalf of the state. Students who want to apply for internships should
contact Peter Aiken (peter.aiken@vcu.edu) for additional information.
!26Copyright 2018 by Data Blueprint Slide #
Virginia Governor's 

Data Interns Program
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
!27Copyright 2017 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
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
IT Project or Application-Centric Development
Original articulation from Doug Bagley @ Walmart
!28Copyright 2018 by Data Blueprint Slide #
Data/
Information
IT

Projects


Strategy
• In support of strategy, organizations
implement IT projects
• Data/information are typically
considered within the scope of IT
projects
• Problems with this approach:
– Ensures data is formed to the applications and
not around the organizational-wide information
requirements
– Process are narrowly formed around
applications
– Very little data reuse is possible
Data-Centric Development
Original articulation from Doug Bagley @ Walmart
!29Copyright 2018 by Data Blueprint Slide #
IT

Projects
Data/

Information


Strategy
• In support of strategy, the organization
develops specific, shared data-based
goals/objectives
• These organizational data goals/
objectives drive the development of
specific IT projects with an eye to
organization-wide usage
• Advantages of this approach:
– Data/information assets are developed from an
organization-wide perspective
– Systems support organizational data needs
and compliment organizational process flows
– Maximum data/information reuse
Data Strategy with Data Governance in Context
!30Copyright 2018 by Data Blueprint Slide #
Organizational

Strategy
Data Strategy
IT Projects
Organizational Operations
Data
Governance
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
!31Copyright 2018 by Data Blueprint Slide #
Organizational

Strategy
Data Strategy
Data
Governance
Data
asset support for 

organizational
strategy
What the data
assets do to support
strategy

How well the data
strategy is working

(Business Goals)
(Metadata)
IT Projects
How data is
delivered by IT
Data Strategy and Governance in Strategic Context
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
!32Copyright 2017 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
t	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
Data is not a Project
• Durable asset
– An asset that has a usable 

life more than one year
• Reasonable project 

deliverables
– 90 day increments
– Data evolution is measured in years
• Data
– Evolves - it is not created
– Significantly more stable
• Readymade data architectural components
– Prerequisite to agile development
• Only alternative is to create additional data siloes!
!33Copyright 2018 by Data Blueprint Slide #
Verification
Maintenance
Systems Development (as described by Winston Royce)
!34Copyright 2018 by Data Blueprint Slide #
Requirements
Design
Implementation
Requirements
Design
Requirements
DesignDesign
Implementation
Design
Requirements
Design
Implementation
$ ...
Project Implementation
!35Copyright 2018 by Data Blueprint Slide #
Develop/Implement 

Software
Develop/Implement Data
This approach can only work when 

no sharing of data occurs!
!35
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
Projects Are Silos
Copyright 2018 by Data Blueprint Slide #
Project 1 Project 2
Shared data structures require programmatic
development and evaluation
Project 3
X XX X X X
X
X XX X
Differences between Programs and Projects
• Programs are Ongoing, Projects End
– Managing a program involves long term strategic planning and 

continuous process improvement is not required of a project
• Programs are Tied to the Financial Calendar
– Program managers are often responsible for delivering 

results tied to the organization's financial calendar
• Program Management is Governance Intensive
– Programs are governed by a senior board that provides direction, 

oversight, and control while projects tend to be less governance-intensive
• Programs Have Greater Scope of Financial Management
– Projects typically have a straight-forward budget and project financial
management is focused on spending to budget while program planning,
management and control is significantly more complex
• Program Change Management is an Executive Leadership Capability
– Projects employ a formal change management process while at the program
level, change management requires executive leadership skills and program
change is driven more by an organization's strategy and is subject to market
conditions and changing business goals
!37Copyright 2018 by Data Blueprint Slide #
Adapted from http://top.idownloadnew.com/program_vs_project/ and http://management.simplicable.com/management/new/program-management-vs-project-management
Your data program
must last at least as
long as your HR
program!
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
!38Copyright 2017 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 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
Data ...
• As a subject is
– Complex and detailed
– Taught inconsistently, and
– Poorly understood
!39Copyright 2018 by Data Blueprint Slide #
What do we teach knowledge workers about data?
!40Copyright 2018 by Data Blueprint Slide #
What percentage of the deal with it daily?
Tacoma Narrows Bridge/Gallopin' Gertie
• Slender, elegant and graceful
• World's 3rd longest suspension span
• Opened on July 1st, collapsed in a windstorm on
November 7, 1940
• "The most dramatic failure in 

bridge engineering history"
• Changed forever how engineers 

design suspension bridges leading 

to safer spans today.
!41Copyright 2018 by Data Blueprint Slide #
!42Copyright 2018 by Data Blueprint Slide #
Similarly data failures cost organizations
minimally 20-40% of their IT budget
Data Footprints
• SQL Server
– 47,000,000,000,000 bytes
– Largest table 34 billion records 3.5 TBs
• Informix
– 1,800,000,000 queries/day
– 65,000,000 tables / 517,000 databases
• Teradata
– 117 billion records
– 23 TBs for one table
• DB2
– 29,838,518,078 daily queries
!43Copyright 2018 by Data Blueprint Slide #
Running Query
!44Copyright 2018 by Data Blueprint Slide #
Optimized Query
!45Copyright 2018 by Data Blueprint Slide #
Repeat 100s, thousands, millions of times ...
!46Copyright 2018 by Data Blueprint Slide #
!47Copyright 2018 by Data Blueprint Slide #
Data is a hidden IT Expense
• Organizations spend between 20 -
40% of their IT budget evolving
their data - including:
– Data migration
• Changing the location from one place to
another
– Data conversion
• Changing data into another form, state, or
product
– Data improving
• Inspecting and manipulating, or re-keying
data to prepare it for subsequent use
– Source: John Zachman
!48Copyright 2018 by Data Blueprint Slide #
PETER AIKEN WITH JUANITA BILLINGS
FOREWORD BY JOHN BOTTEGA
MONETIZING
DATA MANAGEMENT
Unlocking the Value in Your Organization’s
Most Important Asset.
What do we teach IT professionals about data?
!49Copyright 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
!50Copyright 2018 by Data Blueprint Slide #
If the only tool you
know is a hammer
you tend to see
every problem as a
nail (slightly reworded
from Abraham Maslow)
Hiring Panels Are Often
Challenged to Help
!51Copyright 2018 by Data Blueprint Slide #
• Dedicated solely to data asset leveraging
• Unconstrained by an IT project mindset
• Reporting to the business
• 90 Percent of Large Global Organizations Will Have Appointed Chief Data Officers By 2019 

(Gartner website accessed January 26, 2016 http://www.gartner.com/newsroom/id/3190117?)


Top
Operations
Job
Top Data Job
!52Copyright 2018 by Data Blueprint Slide #


Top Job


Top 

Finance 

Job


Top

IT

Job


Top
Marketing
Job


Data Governance Organization


Top

Data 

Job


Enterprise

Data 

Executive


Chief 

Data 

Officer

The Enterprise Data Executive Takes One for the Team
!53Copyright 2018 by Data Blueprint Slide #
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
!54Copyright 2017 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
theDataDoctrine.com
We are uncovering better ways of developing

IT systems by doing it and helping others do it.

Through this work we have come to value:

Data programmes preceding software development
Stable data structures preceding stable code
Shared data preceding completed software
Data reuse preceding reusable code
!55Copyright 2018 by Data Blueprint Slide #


That is, while there is value in the items on

the right, we value the items on the left more.
Mismatched railroad tracks non aligned
Copyright 2017 by Data Blueprint Slide #
!56
Data programmes preceding software development
Data programmes preceding software development
!57Copyright 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 management
and software
development must
be separated and
sequenced
theDataDoctrine.com
We are uncovering better ways of developing

IT systems by doing it and helping others do it.

Through this work we have come to value:

Data programmes preceding software development
Stable data structures preceding stable code
Shared data preceding completed software
Data reuse preceding reusable code
!58Copyright 2018 by Data Blueprint Slide #


That is, while there is value in the items on

the right, we value the items on the left more.
Stable data structures preceding stable code
!59Copyright 2018 by Data Blueprint Slide #
Person Job Class
Position
BR1) One EMPLOYEE
can be associated with one
PERSON
BR2) One EMPLOYEE can be
associated with one POSITION
Manual

Job Sharing
Manual

Moon Lighting
Employee
Stable data structures preceding stable code
!60Copyright 2018 by Data Blueprint Slide #
Person Job Class
Employee Position
BR1) Zero, one, or more
EMPLOYEES can be associated
with one PERSON
BR2) Zero, one, or more EMPLOYEES
can be associated with one POSITION
Job Sharing
Moon Lighting
Stable data structures preceding stable code
!61Copyright 2018 by Data Blueprint Slide #
Data structures must be specified prior
software development/acquisition
(Requires 2 structural loops more
than the more flexible data structure)
More flexible data structure Less flexible data structure
theDataDoctrine.com
We are uncovering better ways of developing

IT systems by doing it and helping others do it.

Through this work we have come to value:

Data programmes preceding software development
Stable data structures preceding stable code
Shared data preceding completed software
Data reuse preceding reusable code
!62Copyright 2018 by Data Blueprint Slide #


That is, while there is value in the items on

the right, we value the items on the left more.
Results
Increasing utility of organizational data
Individual IT Project









Requirements
Design
Implement
Requests Results
Individual IT Project









Requirements
Design
Implement
Requests
Results
Individual IT Project









Requirements
Design
Implement
Requests
Organized,
shared data
Organized,
shared data
Organized,
shared data
Shared Data preceding completed software
!63Copyright 2018 by Data Blueprint Slide #
• Over time the:
– Number of requests increase
– Utility of the results increase
– Data's contribution increases
– and is recognized!
Shared data structures
cannot exist without
programmatic development
and evaluation
theDataDoctrine.com
We are uncovering better ways of developing

IT systems by doing it and helping others do it.

Through this work we have come to value:

Data programmes preceding software development
Stable data structures preceding stable code
Shared data preceding completed software
Data reuse preceding reusable code
!64Copyright 2018 by Data Blueprint Slide #


That is, while there is value in the items on

the right, we value the items on the left more.
Program F
Program E
Program H
Program I
domain 2Application
domain 3
Data reuse preceding reusable code
• Reusable software has been valued more than reusable data
• Who makes decisions about the range and scope of common
data usage?
• Change a program
– 9 max changes
• Change data
– Worst case
– (N * (N - 1)) / 2
– (9 * 8)/2 = 36
!65Copyright 2018 by Data Blueprint Slide #
Program D
Program G
Application
theDataDoctrine.com
We are uncovering better ways of developing

IT systems by doing it and helping others do it.

Through this work we have come to value:

Data programmes preceding software development
Stable data structures preceding stable code
Shared data preceding completed software
Data reuse preceding reusable code
!66Copyright 2018 by Data Blueprint Slide #


That is, while there is value in the items on

the right, we value the items on the left more.
Introducing The Data Doctrine
Copyright 2018 by Data Blueprint Slide #
!67
http://www.thedatadoctrine.com
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
Exorcising the Seven Deadly Data Sins
!68Copyright 2018 by Data Blueprint Slide #
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
IT Business
Data
Perceived State of Data
!69Copyright 2018 by Data Blueprint Slide #
Data
Desired To Be State of Data
!70Copyright 2018 by Data Blueprint Slide #
IT Business
The Real State of Data
!71Copyright 2018 by Data Blueprint Slide #
Data
IT Business
It’s your turn!
Use the chat
feature or Twitter
(#dataed) to submit
your questions now!
Questions?
+ =
!72Copyright 2018 by Data Blueprint Slide #
Upcoming Events
January Webinar:

Data Strategy-Best Practices

January 8, 2019 @ 2:00 PM ET

February Webinar:
Data Architecture versus Data Modeling
February 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
!73Copyright 2018 by Data Blueprint Slide #
Brought to you by:
10124 W. Broad Street, Suite C
Glen Allen, Virginia 23060
804.521.4056
Copyright 2018 by Data Blueprint Slide # !74

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 (with Dr. E. F. "Ted" Codd • DAMA International Community Award 2005 Copyright 2018 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.
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 British Statistician (1919-2013) “All models are wrong, ... ... some are useful.” !3Copyright 2018 by Data Blueprint Slide # !4Copyright 2018 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 Link to amazon.com
  • 3. IT Project Failure Rates (1994-2015) Source: Standish Chaos Reports as reported at: http://standishgroup.com !5Copyright 2018 by Data Blueprint Slide # 0% 15% 30% 45% 60% 1994 1996 1998 2000 2002 2004 2006 2008 2010 2011 2012 2013 2014 2015 Failed Challenged Succeeded System HardwareProcessesPeople Software • A set of detailed methods, procedures, and routines established or formulated to carry out a specific activity, perform a duty, or solve a problem. • An organized, purposeful structure regarded as a whole and consisting of interrelated and interdependent elements (components, entities, factors, members, parts, etc.). These elements continually influence one another (directly or indirectly) to maintain their activity and the existence of the system, in order to achieve the goal of the system. 
 http://www.businessdictionary.com/definition/system.html#ixzz23T7LyAjJ System !6Copyright 2018 by Data Blueprint Slide # DataData
  • 4. How much data,
 by the minute! For the entirety of 2017, every minute of every day: • (almost) Seventy thousand hours of Netflix • (almost) a half million tweets • 15+ million texts • 3.5+ million google searches • 103+ million email spams !7Copyright 2018 by Data Blueprint Slide # https://www.domo.com/learn/data-never-sleeps-5 There will never be less data than right now! !8Copyright 2018 by Data Blueprint Slide # As articulated by Micheline Casey
  • 5. !9Copyright 2018 by Data Blueprint Slide # 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 !10Copyright 2017 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
  • 6. Diagnosing Organizational Readiness !11Copyright 2018 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! !12Copyright 2018 by Data Blueprint Slide # Credit: Image credit: Matt Vickers
  • 7. 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 !13Copyright 2018 by Data Blueprint Slide # Change Management & Leadership !14Copyright 2018 by Data Blueprint Slide #
  • 8. 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 !15Copyright 2018 by Data Blueprint Slide # 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 !16Copyright 2017 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
  • 9. The DAMA Guide to the Data Management 
 Body of 
 Knowledge !17Copyright 2018 by Data Blueprint Slide # Data 
 Management Functions fromTheDAMAGuidetotheDataManagementBodyofKnowledge©2009byDAMAInternational • Good enough 
 to criticize – All models 
 are wrong – Some models 
 are useful • Missing two 
 important concepts – Optionality – Dependency Our barn had to pass a foundation inspection • Before further construction could proceed • No IT equivalent !18Copyright 2018 by Data Blueprint Slide #
  • 10. 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 !19Copyright 2018 by Data Blueprint Slide # 
 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 !20Copyright 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
  • 11. Sequencing the Reasons for a Data Strategy !21Copyright 2018 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 What did Rolls Royce Learn • 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? !22Copyright 2018 by Data Blueprint Slide # from Nascar?
  • 12. 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 !23Copyright 2017 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 7 Data Implementation Framework !24Copyright 2018 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
  • 13. Data Management Program Expenses • 5 Data Managers – Each paid $100,000/year – Do they feel obligated to demonstrate $500,000 in benefits annually? • When will you be done? – "It's okay my CIO gave me 5 years!" – Revised benefits goal is $2.5 million Copyright 2018 by Data Blueprint Slide # !25 improving how the state prices and sells its goods and services, and more efficiently matching citizens to benefits when they enroll. “The first year of our data internship partnership has been a success,” said Governor McAuliffe. “The program has helped the state save time and money by making some of our internal processes more efficient and modern. And it has given students valuable real-world experience. I look forward to seeing what the second year of the program can accomplish.” “Data is an important resource that becomes even more critical as technology progresses,” said VCU President Michael Rao, Ph.D. “VCU is uniquely positioned, both in its location and through the wealth of talent at the School of Business, to help state agencies run their data- centric systems more efficiently, while giving our students hands-on practice in the development of data systems.” During their internships, pairs of VCU students work closely with state agency CIOs to identify specific business cases in which data can be used. Participants gain practical experience in using data to drive re-engineering, while participating CIOs have concrete examples of how to make better use of data to provide innovative and less costly services to citizens. "Working with the talented VCU students gave us a different perspective on what the data was telling us,” said Dave Burhop, Deputy Commissioner/CIO of the Virginia Department of Motor Vehicles. “The VCU interns provided an invaluable resource to the Governor’s Coordinating Council on Homelessness,” said Pamela Kestner, Special Advisor on Families, Children and Poverty. “They very effectively reviewed the data assets available in the participating state agencies and identified analytic content that can be used to better serve the homeless population.” “It's always useful to have ‘fresh eyes’ on data that we are used to seeing,” said Jim Rothrock, Commissioner of the Department for Aging and Rehabilitative Services. “Our interns challenged us and the way we interpret data. It was a refreshing and useful, and we cannot wait for new experiences with new students.” The data internships support Governor McAuliffe’s ongoing initiative to provide easier access to open data in Virginia. The internships also support treating data as an enterprise asset, one of four strategic goals of the enterprise information architecture strategy adopted by the Commonwealth in August 2013. Better use of data allows the Commonwealth to identify opportunities to avoid duplicative costs in collecting, maintaining and using information; and to integrate services across agencies and localities to improve responses to constituent needs and optimize government resources. Virginia Secretary of Technology Karen Jackson and CIO of the Commonwealth Nelson Moe are leading the effort on behalf of the state. Students who want to apply for internships should contact Peter Aiken (peter.aiken@vcu.edu) for additional information. !26Copyright 2018 by Data Blueprint Slide # Virginia Governor's 
 Data Interns Program
  • 14. 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 !27Copyright 2017 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 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 IT Project or Application-Centric Development Original articulation from Doug Bagley @ Walmart !28Copyright 2018 by Data Blueprint Slide # Data/ Information IT
 Projects 
 Strategy • In support of strategy, organizations implement IT projects • Data/information are typically considered within the scope of IT projects • Problems with this approach: – Ensures data is formed to the applications and not around the organizational-wide information requirements – Process are narrowly formed around applications – Very little data reuse is possible
  • 15. Data-Centric Development Original articulation from Doug Bagley @ Walmart !29Copyright 2018 by Data Blueprint Slide # IT
 Projects Data/
 Information 
 Strategy • In support of strategy, the organization develops specific, shared data-based goals/objectives • These organizational data goals/ objectives drive the development of specific IT projects with an eye to organization-wide usage • Advantages of this approach: – Data/information assets are developed from an organization-wide perspective – Systems support organizational data needs and compliment organizational process flows – Maximum data/information reuse Data Strategy with Data Governance in Context !30Copyright 2018 by Data Blueprint Slide # Organizational
 Strategy Data Strategy IT Projects Organizational Operations Data Governance 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
  • 16. !31Copyright 2018 by Data Blueprint Slide # Organizational
 Strategy Data Strategy Data Governance Data asset support for 
 organizational strategy What the data assets do to support strategy
 How well the data strategy is working
 (Business Goals) (Metadata) IT Projects How data is delivered by IT Data Strategy and Governance in Strategic Context 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 !32Copyright 2017 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 t 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
  • 17. Data is not a Project • Durable asset – An asset that has a usable 
 life more than one year • Reasonable project 
 deliverables – 90 day increments – Data evolution is measured in years • Data – Evolves - it is not created – Significantly more stable • Readymade data architectural components – Prerequisite to agile development • Only alternative is to create additional data siloes! !33Copyright 2018 by Data Blueprint Slide # Verification Maintenance Systems Development (as described by Winston Royce) !34Copyright 2018 by Data Blueprint Slide # Requirements Design Implementation Requirements Design Requirements DesignDesign Implementation Design Requirements Design Implementation $ ...
  • 18. Project Implementation !35Copyright 2018 by Data Blueprint Slide # Develop/Implement 
 Software Develop/Implement Data This approach can only work when 
 no sharing of data occurs! !35 XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Projects Are Silos Copyright 2018 by Data Blueprint Slide # Project 1 Project 2 Shared data structures require programmatic development and evaluation Project 3 X XX X X X X X XX X
  • 19. Differences between Programs and Projects • Programs are Ongoing, Projects End – Managing a program involves long term strategic planning and 
 continuous process improvement is not required of a project • Programs are Tied to the Financial Calendar – Program managers are often responsible for delivering 
 results tied to the organization's financial calendar • Program Management is Governance Intensive – Programs are governed by a senior board that provides direction, 
 oversight, and control while projects tend to be less governance-intensive • Programs Have Greater Scope of Financial Management – Projects typically have a straight-forward budget and project financial management is focused on spending to budget while program planning, management and control is significantly more complex • Program Change Management is an Executive Leadership Capability – Projects employ a formal change management process while at the program level, change management requires executive leadership skills and program change is driven more by an organization's strategy and is subject to market conditions and changing business goals !37Copyright 2018 by Data Blueprint Slide # Adapted from http://top.idownloadnew.com/program_vs_project/ and http://management.simplicable.com/management/new/program-management-vs-project-management Your data program must last at least as long as your HR program! 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 !38Copyright 2017 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 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
  • 20. Data ... • As a subject is – Complex and detailed – Taught inconsistently, and – Poorly understood !39Copyright 2018 by Data Blueprint Slide # What do we teach knowledge workers about data? !40Copyright 2018 by Data Blueprint Slide # What percentage of the deal with it daily?
  • 21. Tacoma Narrows Bridge/Gallopin' Gertie • Slender, elegant and graceful • World's 3rd longest suspension span • Opened on July 1st, collapsed in a windstorm on November 7, 1940 • "The most dramatic failure in 
 bridge engineering history" • Changed forever how engineers 
 design suspension bridges leading 
 to safer spans today. !41Copyright 2018 by Data Blueprint Slide # !42Copyright 2018 by Data Blueprint Slide # Similarly data failures cost organizations minimally 20-40% of their IT budget
  • 22. Data Footprints • SQL Server – 47,000,000,000,000 bytes – Largest table 34 billion records 3.5 TBs • Informix – 1,800,000,000 queries/day – 65,000,000 tables / 517,000 databases • Teradata – 117 billion records – 23 TBs for one table • DB2 – 29,838,518,078 daily queries !43Copyright 2018 by Data Blueprint Slide # Running Query !44Copyright 2018 by Data Blueprint Slide #
  • 23. Optimized Query !45Copyright 2018 by Data Blueprint Slide # Repeat 100s, thousands, millions of times ... !46Copyright 2018 by Data Blueprint Slide #
  • 24. !47Copyright 2018 by Data Blueprint Slide # Data is a hidden IT Expense • Organizations spend between 20 - 40% of their IT budget evolving their data - including: – Data migration • Changing the location from one place to another – Data conversion • Changing data into another form, state, or product – Data improving • Inspecting and manipulating, or re-keying data to prepare it for subsequent use – Source: John Zachman !48Copyright 2018 by Data Blueprint Slide # PETER AIKEN WITH JUANITA BILLINGS FOREWORD BY JOHN BOTTEGA MONETIZING DATA MANAGEMENT Unlocking the Value in Your Organization’s Most Important Asset.
  • 25. What do we teach IT professionals about data? !49Copyright 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 !50Copyright 2018 by Data Blueprint Slide # If the only tool you know is a hammer you tend to see every problem as a nail (slightly reworded from Abraham Maslow)
  • 26. Hiring Panels Are Often Challenged to Help !51Copyright 2018 by Data Blueprint Slide # • Dedicated solely to data asset leveraging • Unconstrained by an IT project mindset • Reporting to the business • 90 Percent of Large Global Organizations Will Have Appointed Chief Data Officers By 2019 
 (Gartner website accessed January 26, 2016 http://www.gartner.com/newsroom/id/3190117?) 
 Top Operations Job Top Data Job !52Copyright 2018 by Data Blueprint Slide # 
 Top Job 
 Top 
 Finance 
 Job 
 Top
 IT
 Job 
 Top Marketing Job 
 Data Governance Organization 
 Top
 Data 
 Job 
 Enterprise
 Data 
 Executive 
 Chief 
 Data 
 Officer

  • 27. The Enterprise Data Executive Takes One for the Team !53Copyright 2018 by Data Blueprint Slide # 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 !54Copyright 2017 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
  • 28. theDataDoctrine.com We are uncovering better ways of developing
 IT systems by doing it and helping others do it.
 Through this work we have come to value:
 Data programmes preceding software development Stable data structures preceding stable code Shared data preceding completed software Data reuse preceding reusable code !55Copyright 2018 by Data Blueprint Slide # 
 That is, while there is value in the items on
 the right, we value the items on the left more. Mismatched railroad tracks non aligned Copyright 2017 by Data Blueprint Slide # !56 Data programmes preceding software development
  • 29. Data programmes preceding software development !57Copyright 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 management and software development must be separated and sequenced theDataDoctrine.com We are uncovering better ways of developing
 IT systems by doing it and helping others do it.
 Through this work we have come to value:
 Data programmes preceding software development Stable data structures preceding stable code Shared data preceding completed software Data reuse preceding reusable code !58Copyright 2018 by Data Blueprint Slide # 
 That is, while there is value in the items on
 the right, we value the items on the left more.
  • 30. Stable data structures preceding stable code !59Copyright 2018 by Data Blueprint Slide # Person Job Class Position BR1) One EMPLOYEE can be associated with one PERSON BR2) One EMPLOYEE can be associated with one POSITION Manual
 Job Sharing Manual
 Moon Lighting Employee Stable data structures preceding stable code !60Copyright 2018 by Data Blueprint Slide # Person Job Class Employee Position BR1) Zero, one, or more EMPLOYEES can be associated with one PERSON BR2) Zero, one, or more EMPLOYEES can be associated with one POSITION Job Sharing Moon Lighting
  • 31. Stable data structures preceding stable code !61Copyright 2018 by Data Blueprint Slide # Data structures must be specified prior software development/acquisition (Requires 2 structural loops more than the more flexible data structure) More flexible data structure Less flexible data structure theDataDoctrine.com We are uncovering better ways of developing
 IT systems by doing it and helping others do it.
 Through this work we have come to value:
 Data programmes preceding software development Stable data structures preceding stable code Shared data preceding completed software Data reuse preceding reusable code !62Copyright 2018 by Data Blueprint Slide # 
 That is, while there is value in the items on
 the right, we value the items on the left more.
  • 32. Results Increasing utility of organizational data Individual IT Project
 
 
 
 
 Requirements Design Implement Requests Results Individual IT Project
 
 
 
 
 Requirements Design Implement Requests Results Individual IT Project
 
 
 
 
 Requirements Design Implement Requests Organized, shared data Organized, shared data Organized, shared data Shared Data preceding completed software !63Copyright 2018 by Data Blueprint Slide # • Over time the: – Number of requests increase – Utility of the results increase – Data's contribution increases – and is recognized! Shared data structures cannot exist without programmatic development and evaluation theDataDoctrine.com We are uncovering better ways of developing
 IT systems by doing it and helping others do it.
 Through this work we have come to value:
 Data programmes preceding software development Stable data structures preceding stable code Shared data preceding completed software Data reuse preceding reusable code !64Copyright 2018 by Data Blueprint Slide # 
 That is, while there is value in the items on
 the right, we value the items on the left more.
  • 33. Program F Program E Program H Program I domain 2Application domain 3 Data reuse preceding reusable code • Reusable software has been valued more than reusable data • Who makes decisions about the range and scope of common data usage? • Change a program – 9 max changes • Change data – Worst case – (N * (N - 1)) / 2 – (9 * 8)/2 = 36 !65Copyright 2018 by Data Blueprint Slide # Program D Program G Application theDataDoctrine.com We are uncovering better ways of developing
 IT systems by doing it and helping others do it.
 Through this work we have come to value:
 Data programmes preceding software development Stable data structures preceding stable code Shared data preceding completed software Data reuse preceding reusable code !66Copyright 2018 by Data Blueprint Slide # 
 That is, while there is value in the items on
 the right, we value the items on the left more.
  • 34. Introducing The Data Doctrine Copyright 2018 by Data Blueprint Slide # !67 http://www.thedatadoctrine.com 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 Exorcising the Seven Deadly Data Sins !68Copyright 2018 by Data Blueprint Slide # 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
  • 35. IT Business Data Perceived State of Data !69Copyright 2018 by Data Blueprint Slide # Data Desired To Be State of Data !70Copyright 2018 by Data Blueprint Slide # IT Business
  • 36. The Real State of Data !71Copyright 2018 by Data Blueprint Slide # Data IT Business It’s your turn! Use the chat feature or Twitter (#dataed) to submit your questions now! Questions? + = !72Copyright 2018 by Data Blueprint Slide #
  • 37. Upcoming Events January Webinar:
 Data Strategy-Best Practices
 January 8, 2019 @ 2:00 PM ET
 February Webinar: Data Architecture versus Data Modeling February 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 !73Copyright 2018 by Data Blueprint Slide # Brought to you by: 10124 W. Broad Street, Suite C Glen Allen, Virginia 23060 804.521.4056 Copyright 2018 by Data Blueprint Slide # !74