SlideShare a Scribd company logo
Peter Aiken, PhD
Exorcising
the Seven Deadly Data Sins
1
• 30+ years in data management
• Repeated international recognition
• Founder, Data Blueprint (datablueprint.com)
• Associate Professor of IS (vcu.edu)
• DAMA International (dama.org)
• 9 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, Ph.D.
Copyright 2016 by Data Blueprint Slide #
• DAMA International President 2009-2013
• DAMA International Achievement Award 2001 (with
Dr. E. F. "Ted" Codd
• DAMA International Community Award 2005
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
2
Copyright 2016 by Data Blueprint Slide #Copyright 2016 by Data Blueprint Slide # 3
Excerptedfrom

YourDataStrategy
IT Project Failure Rates (1994-2015)
Source: Standish Chaos Reports as reported at: http://standishgroup.com
4Copyright 2016 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
5Copyright 2016 by Data Blueprint Slide #
IT Business
Data
As Is State of Data (as Perceived)
|————— Project-based —————| |——— Program-based ———|
|——————————————— Program-based ——————————————|
6Copyright 2016 by Data Blueprint Slide #
IT Business
Data
|————— Project-based —————|
Desired To Be State of Data (as Understood)
7Copyright 2016 by Data Blueprint Slide #
Organizational

Strategy
Data Strategy
IT Projects
Organizational Operations
Data
Governance
Data Strategy and Data Governance in Context
Data
asset support for 

organizational
strategy
What the
data assets do to
support strategy
How well the data
strategy is working
Operational
feedback
How data is
delivered by IT
How IT
supports strategy
Other
aspects of
organizational
strategy
8Copyright 2016 by Data Blueprint Slide #
Data Strategy
Data Strategy is Implemented in 2 Phases
What the
data assets do to
support strategy
Phase I-Prerequisites
1) Prepare for dramatic change and determined how to do the work
2) Recruit a qualified, knowledgeable enterprise data executive (and
other qualified talent)
3) Eliminate the Seven Deadly Data Sins
Phase II-Iterations (Lather, Rinse, Repeat)
9Copyright 2016 by Data Blueprint Slide #
Tweeting now: #dataed
Exorcising the Seven Deadly Data Sins
9
1. Not Understanding Data-Centric Thinking
2. Lacking Qualified Data Leadership
3. Not implementing a Robust, Programmatic 

Means of Developing Shared Data
4. Not Aligning The Data Program with IT Projects
5. Failing to Adequately Manage Expectations
6. Not Sequencing Data Strategy Implementation
7. Failing To Address Cultural And 

Change Management Challenges
Tweeting now: #dataed
What is a system?
• 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
10Copyright 2016 by Data Blueprint Slide #
System
DataHardwareProcessesPeople Software
There will never
be less data
than right now!
11Copyright 2016 by Data Blueprint Slide #
12Copyright 2016 by Data Blueprint Slide #
Tweeting now: #dataed
Exorcising the Seven Deadly Data Sins
12
1. Not Understanding Data-Centric Thinking
2. Lacking Qualified Data Leadership
3. Not implementing a Robust, Programmatic 

Means of Developing Shared Data
4. Not Aligning The Data Program with IT Projects
5. Failing to Adequately Manage Expectations
6. Not Sequencing Data Strategy Implementation
7. Failing To Address Cultural And 

Change Management Challenges
Tweeting now: #dataed
What do we teach IT professionals about data?
13Copyright 2016 by Data Blueprint Slide #
• 1 course
– How to build a
new database
• What
impressions do IT
professionals get
from this
education?
– Data is a technical
skill that is needed
when developing
new databases
• If we are migrating databases, we are not creating new
databases and we don't need organizational data
management knowledge, skills, and abilities (KSAs).
• If we are implementing a new software package, we are
not creating a new database and therefore we do not
need data management KSAs.
• If we are installing an enterprise resource package
(ERP), we are not creating a new database and therefore
we do not need data management KSAs.


Top
Operations
Job
Top Data Job
14Copyright 2016 by Data Blueprint Slide #


Top Job


Top 

Finance 

Job


Top

IT

Job


Top
Marketing
Job


Data Governance Organization


Top

Data 

Job


Enterprise

Data 

Executive
• Dedicated solely to data asset leveraging
• Unconstrained by an IT project mindset
• Reporting to the business
• There is enough work to justify the function
and not much talent
• The CDO provides significant input to the
Top Information Technology Job
• 25 Percent of Large Global Organizations Will Have
Appointed Chief Data Officers By 2015 Gartner press
release. Gartner website (accessed May 7, 2014). January
30, 2014. http://www.gartner.com/newsroom/ id/2659215?
• By 2020, 60% of CIOs in global organizations will be
supplanted by the Chief Digital Officer (CDO) for the delivery
of IT-enabled products and digital services (IDC)
• 2015 Experian survey of 250 CIOs found 90% of feel that
data is transforming the way they do business, with
some 92% suggesting that the CDO is best placed to define
data strategy and be the guardian of data quality within an
organisation
• 90 Percent of Large Global Organizations Will Have
Appointed Chief Data Officers By 2019 Gartner press
release. Gartner website (accessed January 26, 2016).
January 26, 2016. http://www.gartner.com/newsroom/id/3190117?
Hiring Panels Are Not Qualified to Help
15Copyright 2016 by Data Blueprint Slide #
Unicorn License There Are No Unicorns
16Copyright 2016 by Data Blueprint Slide #
The Enterprise Data Executive Takes One for the Team
17Copyright 2016 by Data Blueprint Slide #
18Copyright 2016 by Data Blueprint Slide #
Tweeting now: #dataed
Exorcising the Seven Deadly Data Sins
18
1. Not Understanding Data-Centric Thinking
2. Lacking Qualified Data Leadership
3. Not implementing a Robust, Programmatic 

Means of Developing Shared Data
4. Not Aligning The Data Program with IT Projects
5. Failing to Adequately Manage Expectations
6. Not Sequencing Data Strategy Implementation
7. Failing To Address Cultural And 

Change Management Challenges
Tweeting now: #dataed
Differences between Programs and Projects
• Programs are Ongoing, Projects End
– Managing a program involves long term strategic planning and 

continuous process improvement that 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 level 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
• Adapted from http://top.idownloadnew.com/program_vs_project/ and 

http://management.simplicable.com/management/new/program-management-vs-project-management
19Copyright 2016 by Data Blueprint Slide #
Project Implementation
20Copyright 2016 by Data Blueprint Slide #
Develop/Implement 

Software
Develop/Implement Data
This approach can only work when 

no sharing of data occurs!
20
Shared data
structures require
programmatic
development and
evaluation
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
21Copyright 2016 by Data Blueprint Slide #
Tweeting now: #dataed
Exorcising the Seven Deadly Data Sins
21
1. Not Understanding Data-Centric Thinking
2. Lacking Qualified Data Leadership
3. Not implementing a Robust, Programmatic 

Means of Developing Shared Data
4. Not Aligning The Data Program with IT Projects
5. Failing to Adequately Manage Expectations
6. Not Sequencing Data Strategy Implementation
7. Failing To Address Cultural And 

Change Management Challenges
Tweeting now: #dataed
IT Project or Application-Centric Development
Original articulation from Doug Bagley @ Walmart
22Copyright 2016 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
23Copyright 2016 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
24Copyright 2016 by Data Blueprint Slide #
Tweeting now: #dataed
Exorcising the Seven Deadly Data Sins
24
1. Not Understanding Data-Centric Thinking
2. Lacking Qualified Data Leadership
3. Not implementing a Robust, Programmatic 

Means of Developing Shared Data
4. Not Aligning The Data Program with IT Projects
5. Failing to Adequately Manage Expectations
6. Not Sequencing Data Strategy Implementation
7. Failing To Address Cultural And 

Change Management Challenges
Tweeting now: #dataed
Data Management Program Expenses
• 5 Data Managers
• $100,000 Annually
• When will you be done?
• "It's okay my CIO gave me 5 years!"
Copyright 2016 by Data Blueprint Slide #
25
Data Implementation Framework
26Copyright 2016 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
27Copyright 2016 by Data Blueprint Slide #
Tweeting now: #dataed
Exorcising the Seven Deadly Data Sins
27
1. Not Understanding Data-Centric Thinking
2. Lacking Qualified Data Leadership
3. Not implementing a Robust, Programmatic 

Means of Developing Shared Data
4. Not Aligning The Data Program with IT Projects
5. Failing to Adequately Manage Expectations
6. Not Sequencing Data Strategy Implementation
7. Failing To Address Cultural And 

Change Management Challenges
Tweeting now: #dataed


V1

Organizations 

without

a formalized

data strategy
V3

Data Strategy: Use data
to create strategic
opportunities

V4

Data Strategy: Get good 

at both V2 and V3
Improve Operations
Innovation
The focus of data strategy should be sequenced
28Copyright 2016 by Data Blueprint Slide #
Only 1 is 10 organizations has a board
approved data strategy!
V2

Data Strategy: Increase
organizational efficiencies/
effectiveness
29Copyright 2016 by Data Blueprint Slide #
Tweeting now: #dataed
Exorcising the Seven Deadly Data Sins
29
1. Not Understanding Data-Centric Thinking
2. Lacking Qualified Data Leadership
3. Not implementing a Robust, Programmatic 

Means of Developing Shared Data
4. Not Aligning The Data Program with IT Projects
5. Failing to Adequately Manage Expectations
6. Not Sequencing Data Strategy Implementation
7. Failing To Address Cultural And 

Change Management Challenges
Tweeting now: #dataed
Changing is Hard
Culture is the biggest impediment to a shift
in organizational thinking about data
30Copyright 2016 by Data Blueprint Slide #
adapted from the Managing Complex Change model by Dr. Mary Lippitt, 1987
the Data Doctrine
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

31Copyright 2016 by Data Blueprint Slide #
the Data Doctrine
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
32Copyright 2016 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 2016 by Data Blueprint Slide #
33
Data programmes preceding software development
Data programmes preceding software projects
34Copyright 2016 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
Stable data structures preceding stable code
35Copyright 2016 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
Person Job Class
Employee Position
BR1) One EMPLOYEE
can be associated with one
PERSON
BR2) One EMPLOYEE can be
associated with one POSITION
Copyright 2016 by Data Blueprint Slide #
Manual

Job Sharing
Manual

Moon Lighting
Stable data structures preceding stable code
Copyright 2016 by Data Blueprint Slide #
Stable data structures preceding stable code
Data structures must be specified prior
software development
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
38Copyright 2016 by Data Blueprint Slide #
• Over time the:
– Number of requests increase
– Utility of the results increase
– Data's contribution increases
– and is recognized!
Program F
Program E
Program H
Program I
domain 2Application
domain 3
Data reuse preceding reusable code
• Reusable data should leverage shared software routines
• Who makes decisions about the range and scope of
common data usage?
39Copyright 2016 by Data Blueprint Slide #
Program D
Program G
Application
International Chemical Company Engine Testing
• $1billion (+) chemical
company
• Develops/manufactures
additives enhancing the
performance of oils and
fuels ...
• ... to enhance engine/
machine performance
– Helps fuels burn cleaner
– Engines run smoother
– Machines last longer
• Tens of thousands of 

tests annually
– Test costs range up to
$250,000!
40Copyright 2016 by Data Blueprint Slide #
Overview of Existing Data Management Process
1.Manual transfer of digital data
2.Manual file movement/duplication
3.Manual data manipulation
4.Disparate synonym reconciliation
5.Tribal knowledge requirements
6.Non-sustainable technology
41Copyright 2016 by Data Blueprint Slide #
1.Manual transfer of digital data
2.Manual file movement/duplication
3.Manual data manipulation
4.Disparate synonym reconciliation
5.Tribal knowledge requirements
6.Non-sustainable technology
Data Integration Solution
• Integrated the existing systems to
easily search on and find similar or
identical tests
• Results:
– Reduced expenses
– Improved competitive edge 

and customer service
– Time savings and improve operational
capabilities
• According to our client’s internal
business case development, they
expect to realize a $25 million gain
each year thanks to this data
integration
42Copyright 2016 by Data Blueprint Slide #
Introducing The Data Doctrine
Copyright 2016 by Data Blueprint Slide #
43
http://www.thedatadoctrine.com
Questions?
It’s your turn!
Use the chat feature or Twitter (#dataed) to submit
your questions to Peter now!
+ =
44Copyright 2016 by Data Blueprint Slide #
Upcoming Events
Data-Centric Strategy & Roadmap

Supercharging Your Business
January 10, 2017 @ 2:00 PM ET/11:00 AM PT
Sign up here:
www.datablueprint.com/webinar-schedule
or www.dataversity.net
45Copyright 2016 by Data Blueprint Slide #
10124 W. Broad Street, Suite C
Glen Allen, Virginia 23060
804.521.4056
Copyright 2016 by Data Blueprint Slide # 46

More Related Content

What's hot

DI&A Slides: Data Lake vs. Data Warehouse
DI&A Slides: Data Lake vs. Data WarehouseDI&A Slides: Data Lake vs. Data Warehouse
DI&A Slides: Data Lake vs. Data Warehouse
DATAVERSITY
 
IT + Line of Business - Driving Faster, Deeper Insights Together
IT + Line of Business - Driving Faster, Deeper Insights TogetherIT + Line of Business - Driving Faster, Deeper Insights Together
IT + Line of Business - Driving Faster, Deeper Insights Together
DATAVERSITY
 
RWDG Slides: Three Approaches to Data Stewardship
RWDG Slides: Three Approaches to Data StewardshipRWDG Slides: Three Approaches to Data Stewardship
RWDG Slides: Three Approaches to Data Stewardship
DATAVERSITY
 
Data Leadership - Stop Talking About Data and Start Making an Impact!
Data Leadership - Stop Talking About Data and Start Making an Impact!Data Leadership - Stop Talking About Data and Start Making an Impact!
Data Leadership - Stop Talking About Data and Start Making an Impact!
DATAVERSITY
 
Self-Service Data Analysis, Data Wrangling, Data Munging, and Data Modeling –...
Self-Service Data Analysis, Data Wrangling, Data Munging, and Data Modeling –...Self-Service Data Analysis, Data Wrangling, Data Munging, and Data Modeling –...
Self-Service Data Analysis, Data Wrangling, Data Munging, and Data Modeling –...
DATAVERSITY
 
LDM Slides: Data Modeling for XML and JSON
LDM Slides: Data Modeling for XML and JSONLDM Slides: Data Modeling for XML and JSON
LDM Slides: Data Modeling for XML and JSON
DATAVERSITY
 
DI&A Webinar: Building a Flexible and Scalable Analytics Architecture
DI&A Webinar: Building a Flexible and Scalable Analytics ArchitectureDI&A Webinar: Building a Flexible and Scalable Analytics Architecture
DI&A Webinar: Building a Flexible and Scalable Analytics Architecture
DATAVERSITY
 
DAS Slides: Building a Future-State Data Architecture Plan - Where to Begin?
DAS Slides: Building a Future-State Data Architecture Plan - Where to Begin?DAS Slides: Building a Future-State Data Architecture Plan - Where to Begin?
DAS Slides: Building a Future-State Data Architecture Plan - Where to Begin?
DATAVERSITY
 
Data-Ed Webinar: Data Quality Strategies - From Data Duckling to Successful Swan
Data-Ed Webinar: Data Quality Strategies - From Data Duckling to Successful SwanData-Ed Webinar: Data Quality Strategies - From Data Duckling to Successful Swan
Data-Ed Webinar: Data Quality Strategies - From Data Duckling to Successful Swan
DATAVERSITY
 
Big Data Strategies – Organizational Structure and Technology
Big Data Strategies – Organizational Structure and TechnologyBig Data Strategies – Organizational Structure and Technology
Big Data Strategies – Organizational Structure and Technology
DATAVERSITY
 
DAMA Webinar: The Theory of Everything - Is it Time to Rethink Data Management?
DAMA Webinar: The Theory of Everything - Is it Time to Rethink Data Management?DAMA Webinar: The Theory of Everything - Is it Time to Rethink Data Management?
DAMA Webinar: The Theory of Everything - Is it Time to Rethink Data Management?
DATAVERSITY
 
LDM Slides: Conceptual Data Models - How to Get the Attention of Business Use...
LDM Slides: Conceptual Data Models - How to Get the Attention of Business Use...LDM Slides: Conceptual Data Models - How to Get the Attention of Business Use...
LDM Slides: Conceptual Data Models - How to Get the Attention of Business Use...
DATAVERSITY
 
CDO Webinar: 2017 Trends in Data Strategy
CDO Webinar: 2017 Trends in Data StrategyCDO Webinar: 2017 Trends in Data Strategy
CDO Webinar: 2017 Trends in Data Strategy
DATAVERSITY
 
Data Modeling, Data Governance, & Data Quality
Data Modeling, Data Governance, & Data QualityData Modeling, Data Governance, & Data Quality
Data Modeling, Data Governance, & Data Quality
DATAVERSITY
 
Data Insights and Analytics Webinar: CDO vs. CAO - What’s the Difference?
Data Insights and Analytics Webinar: CDO vs. CAO - What’s the Difference?Data Insights and Analytics Webinar: CDO vs. CAO - What’s the Difference?
Data Insights and Analytics Webinar: CDO vs. CAO - What’s the Difference?
DATAVERSITY
 
Essential Metadata Strategies
Essential Metadata StrategiesEssential Metadata Strategies
Essential Metadata Strategies
DATAVERSITY
 
LDM Webinar: Data Modeling & Metadata Management
LDM Webinar: Data Modeling & Metadata ManagementLDM Webinar: Data Modeling & Metadata Management
LDM Webinar: Data Modeling & Metadata Management
DATAVERSITY
 
Data Architecture Best Practices for Today’s Rapidly Changing Data Landscape
Data Architecture Best Practices for Today’s Rapidly Changing Data LandscapeData Architecture Best Practices for Today’s Rapidly Changing Data Landscape
Data Architecture Best Practices for Today’s Rapidly Changing Data Landscape
DATAVERSITY
 
Data-Ed Slides: Best Practices in Data Stewardship (Technical)
Data-Ed Slides: Best Practices in Data Stewardship (Technical)Data-Ed Slides: Best Practices in Data Stewardship (Technical)
Data-Ed Slides: Best Practices in Data Stewardship (Technical)
DATAVERSITY
 
Master Data Management - Practical Strategies for Integrating into Your Data ...
Master Data Management - Practical Strategies for Integrating into Your Data ...Master Data Management - Practical Strategies for Integrating into Your Data ...
Master Data Management - Practical Strategies for Integrating into Your Data ...
DATAVERSITY
 

What's hot (20)

DI&A Slides: Data Lake vs. Data Warehouse
DI&A Slides: Data Lake vs. Data WarehouseDI&A Slides: Data Lake vs. Data Warehouse
DI&A Slides: Data Lake vs. Data Warehouse
 
IT + Line of Business - Driving Faster, Deeper Insights Together
IT + Line of Business - Driving Faster, Deeper Insights TogetherIT + Line of Business - Driving Faster, Deeper Insights Together
IT + Line of Business - Driving Faster, Deeper Insights Together
 
RWDG Slides: Three Approaches to Data Stewardship
RWDG Slides: Three Approaches to Data StewardshipRWDG Slides: Three Approaches to Data Stewardship
RWDG Slides: Three Approaches to Data Stewardship
 
Data Leadership - Stop Talking About Data and Start Making an Impact!
Data Leadership - Stop Talking About Data and Start Making an Impact!Data Leadership - Stop Talking About Data and Start Making an Impact!
Data Leadership - Stop Talking About Data and Start Making an Impact!
 
Self-Service Data Analysis, Data Wrangling, Data Munging, and Data Modeling –...
Self-Service Data Analysis, Data Wrangling, Data Munging, and Data Modeling –...Self-Service Data Analysis, Data Wrangling, Data Munging, and Data Modeling –...
Self-Service Data Analysis, Data Wrangling, Data Munging, and Data Modeling –...
 
LDM Slides: Data Modeling for XML and JSON
LDM Slides: Data Modeling for XML and JSONLDM Slides: Data Modeling for XML and JSON
LDM Slides: Data Modeling for XML and JSON
 
DI&A Webinar: Building a Flexible and Scalable Analytics Architecture
DI&A Webinar: Building a Flexible and Scalable Analytics ArchitectureDI&A Webinar: Building a Flexible and Scalable Analytics Architecture
DI&A Webinar: Building a Flexible and Scalable Analytics Architecture
 
DAS Slides: Building a Future-State Data Architecture Plan - Where to Begin?
DAS Slides: Building a Future-State Data Architecture Plan - Where to Begin?DAS Slides: Building a Future-State Data Architecture Plan - Where to Begin?
DAS Slides: Building a Future-State Data Architecture Plan - Where to Begin?
 
Data-Ed Webinar: Data Quality Strategies - From Data Duckling to Successful Swan
Data-Ed Webinar: Data Quality Strategies - From Data Duckling to Successful SwanData-Ed Webinar: Data Quality Strategies - From Data Duckling to Successful Swan
Data-Ed Webinar: Data Quality Strategies - From Data Duckling to Successful Swan
 
Big Data Strategies – Organizational Structure and Technology
Big Data Strategies – Organizational Structure and TechnologyBig Data Strategies – Organizational Structure and Technology
Big Data Strategies – Organizational Structure and Technology
 
DAMA Webinar: The Theory of Everything - Is it Time to Rethink Data Management?
DAMA Webinar: The Theory of Everything - Is it Time to Rethink Data Management?DAMA Webinar: The Theory of Everything - Is it Time to Rethink Data Management?
DAMA Webinar: The Theory of Everything - Is it Time to Rethink Data Management?
 
LDM Slides: Conceptual Data Models - How to Get the Attention of Business Use...
LDM Slides: Conceptual Data Models - How to Get the Attention of Business Use...LDM Slides: Conceptual Data Models - How to Get the Attention of Business Use...
LDM Slides: Conceptual Data Models - How to Get the Attention of Business Use...
 
CDO Webinar: 2017 Trends in Data Strategy
CDO Webinar: 2017 Trends in Data StrategyCDO Webinar: 2017 Trends in Data Strategy
CDO Webinar: 2017 Trends in Data Strategy
 
Data Modeling, Data Governance, & Data Quality
Data Modeling, Data Governance, & Data QualityData Modeling, Data Governance, & Data Quality
Data Modeling, Data Governance, & Data Quality
 
Data Insights and Analytics Webinar: CDO vs. CAO - What’s the Difference?
Data Insights and Analytics Webinar: CDO vs. CAO - What’s the Difference?Data Insights and Analytics Webinar: CDO vs. CAO - What’s the Difference?
Data Insights and Analytics Webinar: CDO vs. CAO - What’s the Difference?
 
Essential Metadata Strategies
Essential Metadata StrategiesEssential Metadata Strategies
Essential Metadata Strategies
 
LDM Webinar: Data Modeling & Metadata Management
LDM Webinar: Data Modeling & Metadata ManagementLDM Webinar: Data Modeling & Metadata Management
LDM Webinar: Data Modeling & Metadata Management
 
Data Architecture Best Practices for Today’s Rapidly Changing Data Landscape
Data Architecture Best Practices for Today’s Rapidly Changing Data LandscapeData Architecture Best Practices for Today’s Rapidly Changing Data Landscape
Data Architecture Best Practices for Today’s Rapidly Changing Data Landscape
 
Data-Ed Slides: Best Practices in Data Stewardship (Technical)
Data-Ed Slides: Best Practices in Data Stewardship (Technical)Data-Ed Slides: Best Practices in Data Stewardship (Technical)
Data-Ed Slides: Best Practices in Data Stewardship (Technical)
 
Master Data Management - Practical Strategies for Integrating into Your Data ...
Master Data Management - Practical Strategies for Integrating into Your Data ...Master Data Management - Practical Strategies for Integrating into Your Data ...
Master Data Management - Practical Strategies for Integrating into Your Data ...
 

Viewers also liked

Data-Ed Slides: Data-Centric Strategy & Roadmap - Supercharging Your Business
Data-Ed Slides: Data-Centric Strategy & Roadmap - Supercharging Your BusinessData-Ed Slides: Data-Centric Strategy & Roadmap - Supercharging Your Business
Data-Ed Slides: Data-Centric Strategy & Roadmap - Supercharging Your Business
DATAVERSITY
 
Data-Ed Slides: Data Architecture Strategies - Constructing Your Data Garden
Data-Ed Slides: Data Architecture Strategies - Constructing Your Data GardenData-Ed Slides: Data Architecture Strategies - Constructing Your Data Garden
Data-Ed Slides: Data Architecture Strategies - Constructing Your Data Garden
DATAVERSITY
 
Data Strategy
Data StrategyData Strategy
Data Strategy
Jeff Block
 
8 Steps to Creating a Data Strategy
8 Steps to Creating a Data Strategy8 Steps to Creating a Data Strategy
8 Steps to Creating a Data Strategy
Silicon Valley Data Science
 
UML for Data Architects
UML for Data ArchitectsUML for Data Architects
UML for Data Architects
Vladimir Bacvanski, PhD
 
Dache: A Data Aware Caching for Big-Data Applications Using the MapReduce Fra...
Dache: A Data Aware Caching for Big-Data Applications Usingthe MapReduce Fra...Dache: A Data Aware Caching for Big-Data Applications Usingthe MapReduce Fra...
Dache: A Data Aware Caching for Big-Data Applications Using the MapReduce Fra...
Govt.Engineering college, Idukki
 
UML and Data Modeling - A Reconciliation
UML and Data Modeling - A ReconciliationUML and Data Modeling - A Reconciliation
UML and Data Modeling - A Reconciliation
dmurph4
 
DataEd Webinar: Implementing Successful Data Strategies - Developing Organiza...
DataEd Webinar: Implementing Successful Data Strategies - Developing Organiza...DataEd Webinar: Implementing Successful Data Strategies - Developing Organiza...
DataEd Webinar: Implementing Successful Data Strategies - Developing Organiza...
DATAVERSITY
 
Vital AI: Big Data Modeling
Vital AI: Big Data ModelingVital AI: Big Data Modeling
Vital AI: Big Data Modeling
Vital.AI
 
Data strategy in a Big Data world
Data strategy in a Big Data worldData strategy in a Big Data world
Data strategy in a Big Data world
Craig Milroy
 
LDM Webinar: UML for Data Modeling – When Does it Make Sense?
LDM Webinar: UML for Data Modeling – When Does it Make Sense?LDM Webinar: UML for Data Modeling – When Does it Make Sense?
LDM Webinar: UML for Data Modeling – When Does it Make Sense?
DATAVERSITY
 
Data Governance
Data GovernanceData Governance
Data Governance
SambaSoup
 
Big Data Modeling
Big Data ModelingBig Data Modeling
Big Data Modeling
Hans Hultgren
 
A New Way of Thinking About MDM
A New Way of Thinking About MDMA New Way of Thinking About MDM
A New Way of Thinking About MDM
DATAVERSITY
 
A Chant about Classes, Vocab List and Questions Handout
A Chant about Classes, Vocab List and Questions Handout A Chant about Classes, Vocab List and Questions Handout
A Chant about Classes, Vocab List and Questions Handout
Ping Wu
 
Cloudforce Essentials Halifax Keynote - Oct 3
Cloudforce Essentials Halifax Keynote - Oct 3Cloudforce Essentials Halifax Keynote - Oct 3
Cloudforce Essentials Halifax Keynote - Oct 3
nwyne
 
Building Your Follower Ecosystem
Building Your Follower EcosystemBuilding Your Follower Ecosystem
Building Your Follower Ecosystem
LinkedIn For Search and Recruitment Firms
 
新增簡報
新增簡報新增簡報
新增簡報
sysology
 
final research[1][1]
final research[1][1]final research[1][1]
final research[1][1]
Adama Kalokoh
 

Viewers also liked (19)

Data-Ed Slides: Data-Centric Strategy & Roadmap - Supercharging Your Business
Data-Ed Slides: Data-Centric Strategy & Roadmap - Supercharging Your BusinessData-Ed Slides: Data-Centric Strategy & Roadmap - Supercharging Your Business
Data-Ed Slides: Data-Centric Strategy & Roadmap - Supercharging Your Business
 
Data-Ed Slides: Data Architecture Strategies - Constructing Your Data Garden
Data-Ed Slides: Data Architecture Strategies - Constructing Your Data GardenData-Ed Slides: Data Architecture Strategies - Constructing Your Data Garden
Data-Ed Slides: Data Architecture Strategies - Constructing Your Data Garden
 
Data Strategy
Data StrategyData Strategy
Data Strategy
 
8 Steps to Creating a Data Strategy
8 Steps to Creating a Data Strategy8 Steps to Creating a Data Strategy
8 Steps to Creating a Data Strategy
 
UML for Data Architects
UML for Data ArchitectsUML for Data Architects
UML for Data Architects
 
Dache: A Data Aware Caching for Big-Data Applications Using the MapReduce Fra...
Dache: A Data Aware Caching for Big-Data Applications Usingthe MapReduce Fra...Dache: A Data Aware Caching for Big-Data Applications Usingthe MapReduce Fra...
Dache: A Data Aware Caching for Big-Data Applications Using the MapReduce Fra...
 
UML and Data Modeling - A Reconciliation
UML and Data Modeling - A ReconciliationUML and Data Modeling - A Reconciliation
UML and Data Modeling - A Reconciliation
 
DataEd Webinar: Implementing Successful Data Strategies - Developing Organiza...
DataEd Webinar: Implementing Successful Data Strategies - Developing Organiza...DataEd Webinar: Implementing Successful Data Strategies - Developing Organiza...
DataEd Webinar: Implementing Successful Data Strategies - Developing Organiza...
 
Vital AI: Big Data Modeling
Vital AI: Big Data ModelingVital AI: Big Data Modeling
Vital AI: Big Data Modeling
 
Data strategy in a Big Data world
Data strategy in a Big Data worldData strategy in a Big Data world
Data strategy in a Big Data world
 
LDM Webinar: UML for Data Modeling – When Does it Make Sense?
LDM Webinar: UML for Data Modeling – When Does it Make Sense?LDM Webinar: UML for Data Modeling – When Does it Make Sense?
LDM Webinar: UML for Data Modeling – When Does it Make Sense?
 
Data Governance
Data GovernanceData Governance
Data Governance
 
Big Data Modeling
Big Data ModelingBig Data Modeling
Big Data Modeling
 
A New Way of Thinking About MDM
A New Way of Thinking About MDMA New Way of Thinking About MDM
A New Way of Thinking About MDM
 
A Chant about Classes, Vocab List and Questions Handout
A Chant about Classes, Vocab List and Questions Handout A Chant about Classes, Vocab List and Questions Handout
A Chant about Classes, Vocab List and Questions Handout
 
Cloudforce Essentials Halifax Keynote - Oct 3
Cloudforce Essentials Halifax Keynote - Oct 3Cloudforce Essentials Halifax Keynote - Oct 3
Cloudforce Essentials Halifax Keynote - Oct 3
 
Building Your Follower Ecosystem
Building Your Follower EcosystemBuilding Your Follower Ecosystem
Building Your Follower Ecosystem
 
新增簡報
新增簡報新增簡報
新增簡報
 
final research[1][1]
final research[1][1]final research[1][1]
final research[1][1]
 

Similar to Data-Ed Slides: Exorcising the Seven Deadly Data Sins

DataEd Slides: The Seven Deadly Data Sins
DataEd Slides: The Seven Deadly Data SinsDataEd Slides: The Seven Deadly Data Sins
DataEd Slides: The Seven Deadly Data Sins
DATAVERSITY
 
Data-Ed Webinar: Data Governance Strategies
Data-Ed Webinar: Data Governance StrategiesData-Ed Webinar: Data Governance Strategies
Data-Ed Webinar: Data Governance Strategies
DATAVERSITY
 
Data-Ed Webinar: Data-centric Strategy & Roadmap
Data-Ed Webinar: Data-centric Strategy & RoadmapData-Ed Webinar: Data-centric Strategy & Roadmap
Data-Ed Webinar: Data-centric Strategy & Roadmap
DATAVERSITY
 
DAS Slides: Building a Data Strategy - Practical Steps for Aligning with Busi...
DAS Slides: Building a Data Strategy - Practical Steps for Aligning with Busi...DAS Slides: Building a Data Strategy - Practical Steps for Aligning with Busi...
DAS Slides: Building a Data Strategy - Practical Steps for Aligning with Busi...
DATAVERSITY
 
Building a Data Strategy – Practical Steps for Aligning with Business Goals
Building a Data Strategy – Practical Steps for Aligning with Business GoalsBuilding a Data Strategy – Practical Steps for Aligning with Business Goals
Building a Data Strategy – Practical Steps for Aligning with Business Goals
DATAVERSITY
 
Data-Ed Webinar: Data Modeling Fundamentals
Data-Ed Webinar: Data Modeling FundamentalsData-Ed Webinar: Data Modeling Fundamentals
Data-Ed Webinar: Data Modeling Fundamentals
DATAVERSITY
 
DataEd Slides: Data Management Best Practices
DataEd Slides: Data Management Best PracticesDataEd Slides: Data Management Best Practices
DataEd Slides: Data Management Best Practices
DATAVERSITY
 
DataEd Slides: Data Strategy – Plans Are Useless but Planning Is Invaluable
DataEd Slides: Data Strategy – Plans Are Useless but Planning Is InvaluableDataEd Slides: Data Strategy – Plans Are Useless but Planning Is Invaluable
DataEd Slides: Data Strategy – Plans Are Useless but Planning Is Invaluable
DATAVERSITY
 
DataEd Slides: Expressing Data Improvements as Business Outcomes
DataEd Slides: Expressing Data Improvements as Business OutcomesDataEd Slides: Expressing Data Improvements as Business Outcomes
DataEd Slides: Expressing Data Improvements as Business Outcomes
DATAVERSITY
 
DAS Slides: Self-Service Reporting and Data Prep – Benefits & Risks
DAS Slides: Self-Service Reporting and Data Prep – Benefits & RisksDAS Slides: Self-Service Reporting and Data Prep – Benefits & Risks
DAS Slides: Self-Service Reporting and Data Prep – Benefits & Risks
DATAVERSITY
 
Data Architecture Strategies Webinar: Emerging Trends in Data Architecture – ...
Data Architecture Strategies Webinar: Emerging Trends in Data Architecture – ...Data Architecture Strategies Webinar: Emerging Trends in Data Architecture – ...
Data Architecture Strategies Webinar: Emerging Trends in Data Architecture – ...
DATAVERSITY
 
DataEd Slides: Data Management versus Data Strategy
DataEd Slides:  Data Management versus Data StrategyDataEd Slides:  Data Management versus Data Strategy
DataEd Slides: Data Management versus Data Strategy
DATAVERSITY
 
Data Management vs Data Strategy
Data Management vs Data StrategyData Management vs Data Strategy
Data Management vs Data Strategy
DATAVERSITY
 
Necessary Prerequisites to Data Success
Necessary Prerequisites to Data SuccessNecessary Prerequisites to Data Success
Necessary Prerequisites to Data Success
DATAVERSITY
 
Key Elements of a Successful Data Governance Program
Key Elements of a Successful Data Governance ProgramKey Elements of a Successful Data Governance Program
Key Elements of a Successful Data Governance Program
DATAVERSITY
 
Data-Ed Webinar: Monetizing Data Management - Show Me the Money
Data-Ed Webinar: Monetizing Data Management - Show Me the MoneyData-Ed Webinar: Monetizing Data Management - Show Me the Money
Data-Ed Webinar: Monetizing Data Management - Show Me the Money
DATAVERSITY
 
DAS Slides: Building a Data Strategy – Practical Steps for Aligning with Busi...
DAS Slides: Building a Data Strategy – Practical Steps for Aligning with Busi...DAS Slides: Building a Data Strategy – Practical Steps for Aligning with Busi...
DAS Slides: Building a Data Strategy – Practical Steps for Aligning with Busi...
DATAVERSITY
 
Data-Ed Online Webinar: Business Value from MDM
Data-Ed Online Webinar: Business Value from MDMData-Ed Online Webinar: Business Value from MDM
Data-Ed Online Webinar: Business Value from MDM
DATAVERSITY
 
Data-Ed: Business Value From MDM
Data-Ed: Business Value From MDM Data-Ed: Business Value From MDM
Data-Ed: Business Value From MDM
Data Blueprint
 
Data Governance Strategies - With Great Power Comes Great Accountability
Data Governance Strategies - With Great Power Comes Great AccountabilityData Governance Strategies - With Great Power Comes Great Accountability
Data Governance Strategies - With Great Power Comes Great Accountability
DATAVERSITY
 

Similar to Data-Ed Slides: Exorcising the Seven Deadly Data Sins (20)

DataEd Slides: The Seven Deadly Data Sins
DataEd Slides: The Seven Deadly Data SinsDataEd Slides: The Seven Deadly Data Sins
DataEd Slides: The Seven Deadly Data Sins
 
Data-Ed Webinar: Data Governance Strategies
Data-Ed Webinar: Data Governance StrategiesData-Ed Webinar: Data Governance Strategies
Data-Ed Webinar: Data Governance Strategies
 
Data-Ed Webinar: Data-centric Strategy & Roadmap
Data-Ed Webinar: Data-centric Strategy & RoadmapData-Ed Webinar: Data-centric Strategy & Roadmap
Data-Ed Webinar: Data-centric Strategy & Roadmap
 
DAS Slides: Building a Data Strategy - Practical Steps for Aligning with Busi...
DAS Slides: Building a Data Strategy - Practical Steps for Aligning with Busi...DAS Slides: Building a Data Strategy - Practical Steps for Aligning with Busi...
DAS Slides: Building a Data Strategy - Practical Steps for Aligning with Busi...
 
Building a Data Strategy – Practical Steps for Aligning with Business Goals
Building a Data Strategy – Practical Steps for Aligning with Business GoalsBuilding a Data Strategy – Practical Steps for Aligning with Business Goals
Building a Data Strategy – Practical Steps for Aligning with Business Goals
 
Data-Ed Webinar: Data Modeling Fundamentals
Data-Ed Webinar: Data Modeling FundamentalsData-Ed Webinar: Data Modeling Fundamentals
Data-Ed Webinar: Data Modeling Fundamentals
 
DataEd Slides: Data Management Best Practices
DataEd Slides: Data Management Best PracticesDataEd Slides: Data Management Best Practices
DataEd Slides: Data Management Best Practices
 
DataEd Slides: Data Strategy – Plans Are Useless but Planning Is Invaluable
DataEd Slides: Data Strategy – Plans Are Useless but Planning Is InvaluableDataEd Slides: Data Strategy – Plans Are Useless but Planning Is Invaluable
DataEd Slides: Data Strategy – Plans Are Useless but Planning Is Invaluable
 
DataEd Slides: Expressing Data Improvements as Business Outcomes
DataEd Slides: Expressing Data Improvements as Business OutcomesDataEd Slides: Expressing Data Improvements as Business Outcomes
DataEd Slides: Expressing Data Improvements as Business Outcomes
 
DAS Slides: Self-Service Reporting and Data Prep – Benefits & Risks
DAS Slides: Self-Service Reporting and Data Prep – Benefits & RisksDAS Slides: Self-Service Reporting and Data Prep – Benefits & Risks
DAS Slides: Self-Service Reporting and Data Prep – Benefits & Risks
 
Data Architecture Strategies Webinar: Emerging Trends in Data Architecture – ...
Data Architecture Strategies Webinar: Emerging Trends in Data Architecture – ...Data Architecture Strategies Webinar: Emerging Trends in Data Architecture – ...
Data Architecture Strategies Webinar: Emerging Trends in Data Architecture – ...
 
DataEd Slides: Data Management versus Data Strategy
DataEd Slides:  Data Management versus Data StrategyDataEd Slides:  Data Management versus Data Strategy
DataEd Slides: Data Management versus Data Strategy
 
Data Management vs Data Strategy
Data Management vs Data StrategyData Management vs Data Strategy
Data Management vs Data Strategy
 
Necessary Prerequisites to Data Success
Necessary Prerequisites to Data SuccessNecessary Prerequisites to Data Success
Necessary Prerequisites to Data Success
 
Key Elements of a Successful Data Governance Program
Key Elements of a Successful Data Governance ProgramKey Elements of a Successful Data Governance Program
Key Elements of a Successful Data Governance Program
 
Data-Ed Webinar: Monetizing Data Management - Show Me the Money
Data-Ed Webinar: Monetizing Data Management - Show Me the MoneyData-Ed Webinar: Monetizing Data Management - Show Me the Money
Data-Ed Webinar: Monetizing Data Management - Show Me the Money
 
DAS Slides: Building a Data Strategy – Practical Steps for Aligning with Busi...
DAS Slides: Building a Data Strategy – Practical Steps for Aligning with Busi...DAS Slides: Building a Data Strategy – Practical Steps for Aligning with Busi...
DAS Slides: Building a Data Strategy – Practical Steps for Aligning with Busi...
 
Data-Ed Online Webinar: Business Value from MDM
Data-Ed Online Webinar: Business Value from MDMData-Ed Online Webinar: Business Value from MDM
Data-Ed Online Webinar: Business Value from MDM
 
Data-Ed: Business Value From MDM
Data-Ed: Business Value From MDM Data-Ed: Business Value From MDM
Data-Ed: Business Value From MDM
 
Data Governance Strategies - With Great Power Comes Great Accountability
Data Governance Strategies - With Great Power Comes Great AccountabilityData Governance Strategies - With Great Power Comes Great Accountability
Data Governance Strategies - With Great Power Comes Great Accountability
 

More from DATAVERSITY

Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...
Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...
Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...
DATAVERSITY
 
Data at the Speed of Business with Data Mastering and Governance
Data at the Speed of Business with Data Mastering and GovernanceData at the Speed of Business with Data Mastering and Governance
Data at the Speed of Business with Data Mastering and Governance
DATAVERSITY
 
Exploring Levels of Data Literacy
Exploring Levels of Data LiteracyExploring Levels of Data Literacy
Exploring Levels of Data Literacy
DATAVERSITY
 
Building a Data Strategy – Practical Steps for Aligning with Business Goals
Building a Data Strategy – Practical Steps for Aligning with Business GoalsBuilding a Data Strategy – Practical Steps for Aligning with Business Goals
Building a Data Strategy – Practical Steps for Aligning with Business Goals
DATAVERSITY
 
Make Data Work for You
Make Data Work for YouMake Data Work for You
Make Data Work for You
DATAVERSITY
 
Data Catalogs Are the Answer – What is the Question?
Data Catalogs Are the Answer – What is the Question?Data Catalogs Are the Answer – What is the Question?
Data Catalogs Are the Answer – What is the Question?
DATAVERSITY
 
Data Catalogs Are the Answer – What Is the Question?
Data Catalogs Are the Answer – What Is the Question?Data Catalogs Are the Answer – What Is the Question?
Data Catalogs Are the Answer – What Is the Question?
DATAVERSITY
 
Data Modeling Fundamentals
Data Modeling FundamentalsData Modeling Fundamentals
Data Modeling Fundamentals
DATAVERSITY
 
Showing ROI for Your Analytic Project
Showing ROI for Your Analytic ProjectShowing ROI for Your Analytic Project
Showing ROI for Your Analytic Project
DATAVERSITY
 
How a Semantic Layer Makes Data Mesh Work at Scale
How a Semantic Layer Makes  Data Mesh Work at ScaleHow a Semantic Layer Makes  Data Mesh Work at Scale
How a Semantic Layer Makes Data Mesh Work at Scale
DATAVERSITY
 
Is Enterprise Data Literacy Possible?
Is Enterprise Data Literacy Possible?Is Enterprise Data Literacy Possible?
Is Enterprise Data Literacy Possible?
DATAVERSITY
 
The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...
The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...
The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...
DATAVERSITY
 
Emerging Trends in Data Architecture – What’s the Next Big Thing?
Emerging Trends in Data Architecture – What’s the Next Big Thing?Emerging Trends in Data Architecture – What’s the Next Big Thing?
Emerging Trends in Data Architecture – What’s the Next Big Thing?
DATAVERSITY
 
Data Governance Trends - A Look Backwards and Forwards
Data Governance Trends - A Look Backwards and ForwardsData Governance Trends - A Look Backwards and Forwards
Data Governance Trends - A Look Backwards and Forwards
DATAVERSITY
 
Data Governance Trends and Best Practices To Implement Today
Data Governance Trends and Best Practices To Implement TodayData Governance Trends and Best Practices To Implement Today
Data Governance Trends and Best Practices To Implement Today
DATAVERSITY
 
2023 Trends in Enterprise Analytics
2023 Trends in Enterprise Analytics2023 Trends in Enterprise Analytics
2023 Trends in Enterprise Analytics
DATAVERSITY
 
Data Strategy Best Practices
Data Strategy Best PracticesData Strategy Best Practices
Data Strategy Best Practices
DATAVERSITY
 
Who Should Own Data Governance – IT or Business?
Who Should Own Data Governance – IT or Business?Who Should Own Data Governance – IT or Business?
Who Should Own Data Governance – IT or Business?
DATAVERSITY
 
Data Management Best Practices
Data Management Best PracticesData Management Best Practices
Data Management Best Practices
DATAVERSITY
 
MLOps – Applying DevOps to Competitive Advantage
MLOps – Applying DevOps to Competitive AdvantageMLOps – Applying DevOps to Competitive Advantage
MLOps – Applying DevOps to Competitive Advantage
DATAVERSITY
 

More from DATAVERSITY (20)

Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...
Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...
Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...
 
Data at the Speed of Business with Data Mastering and Governance
Data at the Speed of Business with Data Mastering and GovernanceData at the Speed of Business with Data Mastering and Governance
Data at the Speed of Business with Data Mastering and Governance
 
Exploring Levels of Data Literacy
Exploring Levels of Data LiteracyExploring Levels of Data Literacy
Exploring Levels of Data Literacy
 
Building a Data Strategy – Practical Steps for Aligning with Business Goals
Building a Data Strategy – Practical Steps for Aligning with Business GoalsBuilding a Data Strategy – Practical Steps for Aligning with Business Goals
Building a Data Strategy – Practical Steps for Aligning with Business Goals
 
Make Data Work for You
Make Data Work for YouMake Data Work for You
Make Data Work for You
 
Data Catalogs Are the Answer – What is the Question?
Data Catalogs Are the Answer – What is the Question?Data Catalogs Are the Answer – What is the Question?
Data Catalogs Are the Answer – What is the Question?
 
Data Catalogs Are the Answer – What Is the Question?
Data Catalogs Are the Answer – What Is the Question?Data Catalogs Are the Answer – What Is the Question?
Data Catalogs Are the Answer – What Is the Question?
 
Data Modeling Fundamentals
Data Modeling FundamentalsData Modeling Fundamentals
Data Modeling Fundamentals
 
Showing ROI for Your Analytic Project
Showing ROI for Your Analytic ProjectShowing ROI for Your Analytic Project
Showing ROI for Your Analytic Project
 
How a Semantic Layer Makes Data Mesh Work at Scale
How a Semantic Layer Makes  Data Mesh Work at ScaleHow a Semantic Layer Makes  Data Mesh Work at Scale
How a Semantic Layer Makes Data Mesh Work at Scale
 
Is Enterprise Data Literacy Possible?
Is Enterprise Data Literacy Possible?Is Enterprise Data Literacy Possible?
Is Enterprise Data Literacy Possible?
 
The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...
The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...
The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...
 
Emerging Trends in Data Architecture – What’s the Next Big Thing?
Emerging Trends in Data Architecture – What’s the Next Big Thing?Emerging Trends in Data Architecture – What’s the Next Big Thing?
Emerging Trends in Data Architecture – What’s the Next Big Thing?
 
Data Governance Trends - A Look Backwards and Forwards
Data Governance Trends - A Look Backwards and ForwardsData Governance Trends - A Look Backwards and Forwards
Data Governance Trends - A Look Backwards and Forwards
 
Data Governance Trends and Best Practices To Implement Today
Data Governance Trends and Best Practices To Implement TodayData Governance Trends and Best Practices To Implement Today
Data Governance Trends and Best Practices To Implement Today
 
2023 Trends in Enterprise Analytics
2023 Trends in Enterprise Analytics2023 Trends in Enterprise Analytics
2023 Trends in Enterprise Analytics
 
Data Strategy Best Practices
Data Strategy Best PracticesData Strategy Best Practices
Data Strategy Best Practices
 
Who Should Own Data Governance – IT or Business?
Who Should Own Data Governance – IT or Business?Who Should Own Data Governance – IT or Business?
Who Should Own Data Governance – IT or Business?
 
Data Management Best Practices
Data Management Best PracticesData Management Best Practices
Data Management Best Practices
 
MLOps – Applying DevOps to Competitive Advantage
MLOps – Applying DevOps to Competitive AdvantageMLOps – Applying DevOps to Competitive Advantage
MLOps – Applying DevOps to Competitive Advantage
 

Recently uploaded

What's your strategy? Getting tactical about being strategic.
What's your strategy? Getting tactical about being strategic.What's your strategy? Getting tactical about being strategic.
What's your strategy? Getting tactical about being strategic.
Doug Hall
 
84th Marketing Club (OTC Marketing) Dr.Mahmoud Hamed 23rd Cairo.pdf
84th Marketing Club (OTC Marketing) Dr.Mahmoud Hamed 23rd Cairo.pdf84th Marketing Club (OTC Marketing) Dr.Mahmoud Hamed 23rd Cairo.pdf
84th Marketing Club (OTC Marketing) Dr.Mahmoud Hamed 23rd Cairo.pdf
ahmed614380
 
Cracking the Customer Experience Code.pptx
Cracking the Customer Experience Code.pptxCracking the Customer Experience Code.pptx
Cracking the Customer Experience Code.pptx
Workforce Group
 
AI and Best Use Cases for Your Personal Life.pptx
AI and Best Use Cases for Your Personal Life.pptxAI and Best Use Cases for Your Personal Life.pptx
AI and Best Use Cases for Your Personal Life.pptx
Brian Frerichs
 
21stcenturyskillsframeworkfinalpresentation2-240509214747-71edb7ee.pdf
21stcenturyskillsframeworkfinalpresentation2-240509214747-71edb7ee.pdf21stcenturyskillsframeworkfinalpresentation2-240509214747-71edb7ee.pdf
21stcenturyskillsframeworkfinalpresentation2-240509214747-71edb7ee.pdf
emmanuelpulido003
 
Girls Call Vashi 9910780858 Provide Best And Top Girl Service And No1 in City
Girls Call Vashi 9910780858 Provide Best And Top Girl Service And No1 in CityGirls Call Vashi 9910780858 Provide Best And Top Girl Service And No1 in City
Girls Call Vashi 9910780858 Provide Best And Top Girl Service And No1 in City
77sayre
 
Girls Call Andheri West 9910780858 Provide Best And Top Girl Service And No1 ...
Girls Call Andheri West 9910780858 Provide Best And Top Girl Service And No1 ...Girls Call Andheri West 9910780858 Provide Best And Top Girl Service And No1 ...
Girls Call Andheri West 9910780858 Provide Best And Top Girl Service And No1 ...
margaretblush
 
How Do Flange Adapters Work and Why Are They Essential?
How Do Flange Adapters Work and Why Are They Essential?How Do Flange Adapters Work and Why Are They Essential?
How Do Flange Adapters Work and Why Are They Essential?
Texas Flange
 
Why is Structural Engineering Critical in Disaster Preparedness and Resilienc...
Why is Structural Engineering Critical in Disaster Preparedness and Resilienc...Why is Structural Engineering Critical in Disaster Preparedness and Resilienc...
Why is Structural Engineering Critical in Disaster Preparedness and Resilienc...
grouphirani24
 
Maximise your Business Potential: Annual Planning Workshop
Maximise your Business Potential: Annual Planning WorkshopMaximise your Business Potential: Annual Planning Workshop
Maximise your Business Potential: Annual Planning Workshop
chris908327
 
upGrad_Case_Study_by_Himanshu_Singh.pptx
upGrad_Case_Study_by_Himanshu_Singh.pptxupGrad_Case_Study_by_Himanshu_Singh.pptx
upGrad_Case_Study_by_Himanshu_Singh.pptx
himanshubclubofgsv
 
Qatar Airways Kuwait Office.pdf.........
Qatar Airways Kuwait Office.pdf.........Qatar Airways Kuwait Office.pdf.........
Qatar Airways Kuwait Office.pdf.........
anissageorge9890
 
Gym business MODEL .pdf .
Gym business MODEL .pdf                 .Gym business MODEL .pdf                 .
Gym business MODEL .pdf .
Divyanshu56740
 
Luxury Lifestyle Summit 2024 - Sponsorship
Luxury Lifestyle Summit 2024 - SponsorshipLuxury Lifestyle Summit 2024 - Sponsorship
Luxury Lifestyle Summit 2024 - Sponsorship
uitdiedosfinance
 
AI at Work​ The demystification of AI and real-world stories on how to apply ...
AI at Work​ The demystification of AI and real-world stories on how to apply ...AI at Work​ The demystification of AI and real-world stories on how to apply ...
AI at Work​ The demystification of AI and real-world stories on how to apply ...
Auxis Consulting & Outsourcing
 
Corporate Governance for South African Mining Companies
Corporate Governance for South African Mining CompaniesCorporate Governance for South African Mining Companies
Corporate Governance for South African Mining Companies
James AH Campbell
 
YouTube Automation Step-by-step Guide.pdf
YouTube Automation Step-by-step Guide.pdfYouTube Automation Step-by-step Guide.pdf
YouTube Automation Step-by-step Guide.pdf
grizzyhuncho
 
Top five predictions today, .
Top five predictions today,            .Top five predictions today,            .
Top five predictions today, .
Rupasingh82
 
Standard Operating Procedure for Digital Marketing
Standard Operating Procedure for Digital MarketingStandard Operating Procedure for Digital Marketing
Standard Operating Procedure for Digital Marketing
Dipendra Prasad Poudel
 
Path to the next normal collection McKinsey
Path to the next normal collection McKinseyPath to the next normal collection McKinsey
Path to the next normal collection McKinsey
MajIman2
 

Recently uploaded (20)

What's your strategy? Getting tactical about being strategic.
What's your strategy? Getting tactical about being strategic.What's your strategy? Getting tactical about being strategic.
What's your strategy? Getting tactical about being strategic.
 
84th Marketing Club (OTC Marketing) Dr.Mahmoud Hamed 23rd Cairo.pdf
84th Marketing Club (OTC Marketing) Dr.Mahmoud Hamed 23rd Cairo.pdf84th Marketing Club (OTC Marketing) Dr.Mahmoud Hamed 23rd Cairo.pdf
84th Marketing Club (OTC Marketing) Dr.Mahmoud Hamed 23rd Cairo.pdf
 
Cracking the Customer Experience Code.pptx
Cracking the Customer Experience Code.pptxCracking the Customer Experience Code.pptx
Cracking the Customer Experience Code.pptx
 
AI and Best Use Cases for Your Personal Life.pptx
AI and Best Use Cases for Your Personal Life.pptxAI and Best Use Cases for Your Personal Life.pptx
AI and Best Use Cases for Your Personal Life.pptx
 
21stcenturyskillsframeworkfinalpresentation2-240509214747-71edb7ee.pdf
21stcenturyskillsframeworkfinalpresentation2-240509214747-71edb7ee.pdf21stcenturyskillsframeworkfinalpresentation2-240509214747-71edb7ee.pdf
21stcenturyskillsframeworkfinalpresentation2-240509214747-71edb7ee.pdf
 
Girls Call Vashi 9910780858 Provide Best And Top Girl Service And No1 in City
Girls Call Vashi 9910780858 Provide Best And Top Girl Service And No1 in CityGirls Call Vashi 9910780858 Provide Best And Top Girl Service And No1 in City
Girls Call Vashi 9910780858 Provide Best And Top Girl Service And No1 in City
 
Girls Call Andheri West 9910780858 Provide Best And Top Girl Service And No1 ...
Girls Call Andheri West 9910780858 Provide Best And Top Girl Service And No1 ...Girls Call Andheri West 9910780858 Provide Best And Top Girl Service And No1 ...
Girls Call Andheri West 9910780858 Provide Best And Top Girl Service And No1 ...
 
How Do Flange Adapters Work and Why Are They Essential?
How Do Flange Adapters Work and Why Are They Essential?How Do Flange Adapters Work and Why Are They Essential?
How Do Flange Adapters Work and Why Are They Essential?
 
Why is Structural Engineering Critical in Disaster Preparedness and Resilienc...
Why is Structural Engineering Critical in Disaster Preparedness and Resilienc...Why is Structural Engineering Critical in Disaster Preparedness and Resilienc...
Why is Structural Engineering Critical in Disaster Preparedness and Resilienc...
 
Maximise your Business Potential: Annual Planning Workshop
Maximise your Business Potential: Annual Planning WorkshopMaximise your Business Potential: Annual Planning Workshop
Maximise your Business Potential: Annual Planning Workshop
 
upGrad_Case_Study_by_Himanshu_Singh.pptx
upGrad_Case_Study_by_Himanshu_Singh.pptxupGrad_Case_Study_by_Himanshu_Singh.pptx
upGrad_Case_Study_by_Himanshu_Singh.pptx
 
Qatar Airways Kuwait Office.pdf.........
Qatar Airways Kuwait Office.pdf.........Qatar Airways Kuwait Office.pdf.........
Qatar Airways Kuwait Office.pdf.........
 
Gym business MODEL .pdf .
Gym business MODEL .pdf                 .Gym business MODEL .pdf                 .
Gym business MODEL .pdf .
 
Luxury Lifestyle Summit 2024 - Sponsorship
Luxury Lifestyle Summit 2024 - SponsorshipLuxury Lifestyle Summit 2024 - Sponsorship
Luxury Lifestyle Summit 2024 - Sponsorship
 
AI at Work​ The demystification of AI and real-world stories on how to apply ...
AI at Work​ The demystification of AI and real-world stories on how to apply ...AI at Work​ The demystification of AI and real-world stories on how to apply ...
AI at Work​ The demystification of AI and real-world stories on how to apply ...
 
Corporate Governance for South African Mining Companies
Corporate Governance for South African Mining CompaniesCorporate Governance for South African Mining Companies
Corporate Governance for South African Mining Companies
 
YouTube Automation Step-by-step Guide.pdf
YouTube Automation Step-by-step Guide.pdfYouTube Automation Step-by-step Guide.pdf
YouTube Automation Step-by-step Guide.pdf
 
Top five predictions today, .
Top five predictions today,            .Top five predictions today,            .
Top five predictions today, .
 
Standard Operating Procedure for Digital Marketing
Standard Operating Procedure for Digital MarketingStandard Operating Procedure for Digital Marketing
Standard Operating Procedure for Digital Marketing
 
Path to the next normal collection McKinsey
Path to the next normal collection McKinseyPath to the next normal collection McKinsey
Path to the next normal collection McKinsey
 

Data-Ed Slides: Exorcising the Seven Deadly Data Sins

  • 1. Peter Aiken, PhD Exorcising the Seven Deadly Data Sins 1 • 30+ years in data management • Repeated international recognition • Founder, Data Blueprint (datablueprint.com) • Associate Professor of IS (vcu.edu) • DAMA International (dama.org) • 9 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, Ph.D. Copyright 2016 by Data Blueprint Slide # • DAMA International President 2009-2013 • DAMA International Achievement Award 2001 (with Dr. E. F. "Ted" Codd • DAMA International Community Award 2005 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 2
  • 2. Copyright 2016 by Data Blueprint Slide #Copyright 2016 by Data Blueprint Slide # 3 Excerptedfrom
 YourDataStrategy IT Project Failure Rates (1994-2015) Source: Standish Chaos Reports as reported at: http://standishgroup.com 4Copyright 2016 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
  • 3. 5Copyright 2016 by Data Blueprint Slide # IT Business Data As Is State of Data (as Perceived) |————— Project-based —————| |——— Program-based ———| |——————————————— Program-based ——————————————| 6Copyright 2016 by Data Blueprint Slide # IT Business Data |————— Project-based —————| Desired To Be State of Data (as Understood)
  • 4. 7Copyright 2016 by Data Blueprint Slide # Organizational
 Strategy Data Strategy IT Projects Organizational Operations Data Governance Data Strategy and Data Governance in Context Data asset support for 
 organizational strategy What the data assets do to support strategy How well the data strategy is working Operational feedback How data is delivered by IT How IT supports strategy Other aspects of organizational strategy 8Copyright 2016 by Data Blueprint Slide # Data Strategy Data Strategy is Implemented in 2 Phases What the data assets do to support strategy Phase I-Prerequisites 1) Prepare for dramatic change and determined how to do the work 2) Recruit a qualified, knowledgeable enterprise data executive (and other qualified talent) 3) Eliminate the Seven Deadly Data Sins Phase II-Iterations (Lather, Rinse, Repeat)
  • 5. 9Copyright 2016 by Data Blueprint Slide # Tweeting now: #dataed Exorcising the Seven Deadly Data Sins 9 1. Not Understanding Data-Centric Thinking 2. Lacking Qualified Data Leadership 3. Not implementing a Robust, Programmatic 
 Means of Developing Shared Data 4. Not Aligning The Data Program with IT Projects 5. Failing to Adequately Manage Expectations 6. Not Sequencing Data Strategy Implementation 7. Failing To Address Cultural And 
 Change Management Challenges Tweeting now: #dataed What is a system? • 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 10Copyright 2016 by Data Blueprint Slide # System DataHardwareProcessesPeople Software
  • 6. There will never be less data than right now! 11Copyright 2016 by Data Blueprint Slide # 12Copyright 2016 by Data Blueprint Slide # Tweeting now: #dataed Exorcising the Seven Deadly Data Sins 12 1. Not Understanding Data-Centric Thinking 2. Lacking Qualified Data Leadership 3. Not implementing a Robust, Programmatic 
 Means of Developing Shared Data 4. Not Aligning The Data Program with IT Projects 5. Failing to Adequately Manage Expectations 6. Not Sequencing Data Strategy Implementation 7. Failing To Address Cultural And 
 Change Management Challenges Tweeting now: #dataed
  • 7. What do we teach IT professionals about data? 13Copyright 2016 by Data Blueprint Slide # • 1 course – How to build a new database • What impressions do IT professionals get from this education? – Data is a technical skill that is needed when developing new databases • If we are migrating databases, we are not creating new databases and we don't need organizational data management knowledge, skills, and abilities (KSAs). • If we are implementing a new software package, we are not creating a new database and therefore we do not need data management KSAs. • If we are installing an enterprise resource package (ERP), we are not creating a new database and therefore we do not need data management KSAs. 
 Top Operations Job Top Data Job 14Copyright 2016 by Data Blueprint Slide # 
 Top Job 
 Top 
 Finance 
 Job 
 Top
 IT
 Job 
 Top Marketing Job 
 Data Governance Organization 
 Top
 Data 
 Job 
 Enterprise
 Data 
 Executive • Dedicated solely to data asset leveraging • Unconstrained by an IT project mindset • Reporting to the business • There is enough work to justify the function and not much talent • The CDO provides significant input to the Top Information Technology Job • 25 Percent of Large Global Organizations Will Have Appointed Chief Data Officers By 2015 Gartner press release. Gartner website (accessed May 7, 2014). January 30, 2014. http://www.gartner.com/newsroom/ id/2659215? • By 2020, 60% of CIOs in global organizations will be supplanted by the Chief Digital Officer (CDO) for the delivery of IT-enabled products and digital services (IDC) • 2015 Experian survey of 250 CIOs found 90% of feel that data is transforming the way they do business, with some 92% suggesting that the CDO is best placed to define data strategy and be the guardian of data quality within an organisation • 90 Percent of Large Global Organizations Will Have Appointed Chief Data Officers By 2019 Gartner press release. Gartner website (accessed January 26, 2016). January 26, 2016. http://www.gartner.com/newsroom/id/3190117?
  • 8. Hiring Panels Are Not Qualified to Help 15Copyright 2016 by Data Blueprint Slide # Unicorn License There Are No Unicorns 16Copyright 2016 by Data Blueprint Slide #
  • 9. The Enterprise Data Executive Takes One for the Team 17Copyright 2016 by Data Blueprint Slide # 18Copyright 2016 by Data Blueprint Slide # Tweeting now: #dataed Exorcising the Seven Deadly Data Sins 18 1. Not Understanding Data-Centric Thinking 2. Lacking Qualified Data Leadership 3. Not implementing a Robust, Programmatic 
 Means of Developing Shared Data 4. Not Aligning The Data Program with IT Projects 5. Failing to Adequately Manage Expectations 6. Not Sequencing Data Strategy Implementation 7. Failing To Address Cultural And 
 Change Management Challenges Tweeting now: #dataed
  • 10. Differences between Programs and Projects • Programs are Ongoing, Projects End – Managing a program involves long term strategic planning and 
 continuous process improvement that 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 level 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 • Adapted from http://top.idownloadnew.com/program_vs_project/ and 
 http://management.simplicable.com/management/new/program-management-vs-project-management 19Copyright 2016 by Data Blueprint Slide # Project Implementation 20Copyright 2016 by Data Blueprint Slide # Develop/Implement 
 Software Develop/Implement Data This approach can only work when 
 no sharing of data occurs! 20 Shared data structures require programmatic development and evaluation XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
  • 11. 21Copyright 2016 by Data Blueprint Slide # Tweeting now: #dataed Exorcising the Seven Deadly Data Sins 21 1. Not Understanding Data-Centric Thinking 2. Lacking Qualified Data Leadership 3. Not implementing a Robust, Programmatic 
 Means of Developing Shared Data 4. Not Aligning The Data Program with IT Projects 5. Failing to Adequately Manage Expectations 6. Not Sequencing Data Strategy Implementation 7. Failing To Address Cultural And 
 Change Management Challenges Tweeting now: #dataed IT Project or Application-Centric Development Original articulation from Doug Bagley @ Walmart 22Copyright 2016 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
  • 12. Data-Centric Development Original articulation from Doug Bagley @ Walmart 23Copyright 2016 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 24Copyright 2016 by Data Blueprint Slide # Tweeting now: #dataed Exorcising the Seven Deadly Data Sins 24 1. Not Understanding Data-Centric Thinking 2. Lacking Qualified Data Leadership 3. Not implementing a Robust, Programmatic 
 Means of Developing Shared Data 4. Not Aligning The Data Program with IT Projects 5. Failing to Adequately Manage Expectations 6. Not Sequencing Data Strategy Implementation 7. Failing To Address Cultural And 
 Change Management Challenges Tweeting now: #dataed
  • 13. Data Management Program Expenses • 5 Data Managers • $100,000 Annually • When will you be done? • "It's okay my CIO gave me 5 years!" Copyright 2016 by Data Blueprint Slide # 25 Data Implementation Framework 26Copyright 2016 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
  • 14. 27Copyright 2016 by Data Blueprint Slide # Tweeting now: #dataed Exorcising the Seven Deadly Data Sins 27 1. Not Understanding Data-Centric Thinking 2. Lacking Qualified Data Leadership 3. Not implementing a Robust, Programmatic 
 Means of Developing Shared Data 4. Not Aligning The Data Program with IT Projects 5. Failing to Adequately Manage Expectations 6. Not Sequencing Data Strategy Implementation 7. Failing To Address Cultural And 
 Change Management Challenges Tweeting now: #dataed 
 V1
 Organizations 
 without
 a formalized
 data strategy V3
 Data Strategy: Use data to create strategic opportunities
 V4
 Data Strategy: Get good 
 at both V2 and V3 Improve Operations Innovation The focus of data strategy should be sequenced 28Copyright 2016 by Data Blueprint Slide # Only 1 is 10 organizations has a board approved data strategy! V2
 Data Strategy: Increase organizational efficiencies/ effectiveness
  • 15. 29Copyright 2016 by Data Blueprint Slide # Tweeting now: #dataed Exorcising the Seven Deadly Data Sins 29 1. Not Understanding Data-Centric Thinking 2. Lacking Qualified Data Leadership 3. Not implementing a Robust, Programmatic 
 Means of Developing Shared Data 4. Not Aligning The Data Program with IT Projects 5. Failing to Adequately Manage Expectations 6. Not Sequencing Data Strategy Implementation 7. Failing To Address Cultural And 
 Change Management Challenges Tweeting now: #dataed Changing is Hard Culture is the biggest impediment to a shift in organizational thinking about data 30Copyright 2016 by Data Blueprint Slide # adapted from the Managing Complex Change model by Dr. Mary Lippitt, 1987
  • 16. the Data Doctrine 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
 31Copyright 2016 by Data Blueprint Slide # the Data Doctrine 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 32Copyright 2016 by Data Blueprint Slide # 
 That is, while there is value in the items on
 the right, we value the items on the left more.
  • 17. Mismatched railroad tracks non aligned Copyright 2016 by Data Blueprint Slide # 33 Data programmes preceding software development Data programmes preceding software projects 34Copyright 2016 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
  • 18. Stable data structures preceding stable code 35Copyright 2016 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 Person Job Class Employee Position BR1) One EMPLOYEE can be associated with one PERSON BR2) One EMPLOYEE can be associated with one POSITION Copyright 2016 by Data Blueprint Slide # Manual
 Job Sharing Manual
 Moon Lighting Stable data structures preceding stable code
  • 19. Copyright 2016 by Data Blueprint Slide # Stable data structures preceding stable code Data structures must be specified prior software development 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 38Copyright 2016 by Data Blueprint Slide # • Over time the: – Number of requests increase – Utility of the results increase – Data's contribution increases – and is recognized!
  • 20. Program F Program E Program H Program I domain 2Application domain 3 Data reuse preceding reusable code • Reusable data should leverage shared software routines • Who makes decisions about the range and scope of common data usage? 39Copyright 2016 by Data Blueprint Slide # Program D Program G Application International Chemical Company Engine Testing • $1billion (+) chemical company • Develops/manufactures additives enhancing the performance of oils and fuels ... • ... to enhance engine/ machine performance – Helps fuels burn cleaner – Engines run smoother – Machines last longer • Tens of thousands of 
 tests annually – Test costs range up to $250,000! 40Copyright 2016 by Data Blueprint Slide #
  • 21. Overview of Existing Data Management Process 1.Manual transfer of digital data 2.Manual file movement/duplication 3.Manual data manipulation 4.Disparate synonym reconciliation 5.Tribal knowledge requirements 6.Non-sustainable technology 41Copyright 2016 by Data Blueprint Slide # 1.Manual transfer of digital data 2.Manual file movement/duplication 3.Manual data manipulation 4.Disparate synonym reconciliation 5.Tribal knowledge requirements 6.Non-sustainable technology Data Integration Solution • Integrated the existing systems to easily search on and find similar or identical tests • Results: – Reduced expenses – Improved competitive edge 
 and customer service – Time savings and improve operational capabilities • According to our client’s internal business case development, they expect to realize a $25 million gain each year thanks to this data integration 42Copyright 2016 by Data Blueprint Slide #
  • 22. Introducing The Data Doctrine Copyright 2016 by Data Blueprint Slide # 43 http://www.thedatadoctrine.com Questions? It’s your turn! Use the chat feature or Twitter (#dataed) to submit your questions to Peter now! + = 44Copyright 2016 by Data Blueprint Slide #
  • 23. Upcoming Events Data-Centric Strategy & Roadmap
 Supercharging Your Business January 10, 2017 @ 2:00 PM ET/11:00 AM PT Sign up here: www.datablueprint.com/webinar-schedule or www.dataversity.net 45Copyright 2016 by Data Blueprint Slide # 10124 W. Broad Street, Suite C Glen Allen, Virginia 23060 804.521.4056 Copyright 2016 by Data Blueprint Slide # 46