How to Implement Data Governance Best Practice

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Copyright © 2012 Robert S. Seiner – KIK Consulting & Educational Services / TDAN.com
Non-Invasive Data Governance™ is a trademark of Robert S. Seiner & KIK Consulting
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Robert S. Seiner
KIK Consulting & Educational Services – KIKconsulting.com
The Data Administration Newsletter – TDAN.com
Real-World Data Governance
How to Implement
Data Governance Best Practice
Monthly Webinar Series Hosted by Dataversity
April 21, 2016 – 2:00 p.m. EST

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• Real-World Data Governance – Monthly Webinar Series
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– May 19, 2016 – A Data Governance Framework for Smart Data w/Tony Sarris
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Introduction
• Data Governance Best Practice is defined as basis and guidelines for
suggested governing activities.
• Organizations define best practices to be used as a point of comparison
when determining their readiness, willingness and actions necessary to put
a Data Governance program in place.
• But what are the best practices and how can they be implemented? This
webinar will address these questions and more.

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Introduction
• This webinar covers:
– Two Criteria for Data Governance Best Practice Development
– How to Assess against Best Practice to Build Program Success
– Examples of Industry Selected DG Best Practice
– How to Communicate DG Best Practice in a Non-Threatening Way
– How to Build DG Best Practice into Daily Operations

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Definitions
• Data Governance
– Data Governance is the Execution and Enforcement of Authority
Over the Management of Data and Data-Related Resources.

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Definitions
• Data Stewardship
– Data Stewardship is the Formalization of Accountability
Over the Management of Data and Data-Related Resources.

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Definitions
• Non-Invasive Data Governance™
– The practice of:
• formalizing accountability & behavior
• recognizing non-invasive roles & responsibilities
• applying discipline to existing and/or new processes
• assuring that the definition, production & usage of data
• assures regulatory compliance, security, privacy, protection & quality.
– Non-Invasive describes how governance is applied to assure
non-threatening management of data assets.
– The goal is to be
• Transparent
• Supportive
• Collaborative.

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• What to Tell Management:
– We ARE already governing data (but we are doing it informally, inefficiently, ineffectively).
– We CAN formalize how we govern data by putting structure around what we are
presently doing.
– We CAN Improve …
• How We Manage Data Risk & Protect Data
• Data Quality & Provide Quality Assurance
• Coordination & Cooperation Around Data
• Communications and Understanding Around Data
– We DO NOT Have to Spend a lot of Money.
In fact … Data Governance only costs the time we put into it.
– We NEED structure. We should consider a Non-Invasive approach.
Best Practice Messages

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• What NOT to Tell Management
– Do NOT Sell Data Governance as being a Huge Challenge.
– Emphasize that Data Governance is NOT a Technical Solution.
– Emphasize again that People Behavior is Governed, NOT Data.
– Emphasize that Data Governance is an Evolution, NOT Revolution.

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• [to] gov·ern [data]
v. gov·erned, gov·ern·ing, gov·erns
– To make and administer the public policy and affairs
– To exercise sovereign authority
– To control the speed or magnitude
– To regulate
– To control the actions or behavior
– To keep under control; to restrain
– To exercise a deciding or determining influence
– To exercise political authority
– To have or exercise a determining influence
FreeDictionary.com

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Creating Best Practice
• Best Practice Overview & Assessment Process
– Data Governance Best Practice are defined as the basis and guideline for
behavior to deliver Data Governance Programs.
1. Organizations that successfully implement Data Governance Programs begin by
defining a limited series of best practice before assessing their present practices
in comparison to the best practice.
2. Once the best practice is defined, an assessment must be completed to identify:
 The GAP between the Best Practice and the present practices.
 The RISKS (and potential risks) associated with the gap.

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• Criteria to Determining if a Statement is a Best Practice
– Is the Statement Practical, Do-able and will it Add Value?
Answer should be “Yes” or best practice statement should not be considered.
– Is the Program At Risk if the practice is not achieved?
Answer should be “Yes” or best practice statement should not be considered.

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• Best Practice Around Creating a Best Practice Document
– First Document Created for Data Governance
– Basis of the Assessment
– Underline words to be defined elsewhere
– Present tense versus Future tense
– Typically 4-6 Best Practice
– Analyze from a Business and Technical Perspective
– Verbose versus To The Point

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• Best Practice from an Insurance Company:
– There is a High-Level of Senior Management Support, Sponsorship, and
Understanding of the activities of the Program and Team.
– A team of cross-Departmental resources as well as a dedicated program manager
are accountable for the definition, development, implementation and
sustainability of the Program on a consistent and continual basis. This group will
be known as the Planning Team during the program development phase and as
the Program Team upon deployment of the program.
– The measurements of success (and how they will be measured) of the program
are well defined and communicated with Senior Management and Stakeholders
within the organization.
– The goals, objectives, scope, roles & responsibilities, and Rules of Engagement of
the Program and Team are well defined and communicated.

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• Best Practice from a Government Agency:
– Senior Management supports, sponsors and understands (at a high-level) Data
Governance activities for protecting data.
– Data Governance protecting data is applied consistently across the Department.
(Minimum standards must be adhered to; standard can be exceeded).
– Resources are allocated to define, develop and sustain Data Governance.
– Policies and procedures assure protection of data is not optional.
– Internal and External Stakeholders are informed of program goals, scope, roles &
responsibilities, expectations, and performance measurements.

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• Best Practice from an Education Company:
– For Data Governance to be successful there will need to be a High Level of Senior
Management Support and Understanding of the activities of the Data
Governance Team, the roles defined in the Data Governance Operating Model,
and specific examples of where Data Governance will add value.
– Select staff must be committed to the definition, development, execution and
sustainability of the Data Governance Program on a continual basis. This group
will be known as the Data Governance Team and will be lead by Information
Technology in partnership with Corporate Risk Governance with subject matter
expertise from Strategic Business Units and Shared Corporate Functions.
– The Data Governance Principles will be applied consistently and continuously to
data that is defined, produced and used for Enterprise Reporting. The initial
focus of the Data Governance Program will be directed at improving the quality,
understandability and value of data that drives metrics for Academics Reporting.
•

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• Sample Best Practices Summary:
1. Senior Management Support, Sponsorship & Understanding
2. Resources Must Be Applied
3. Roles & Responsibilities Must Be Clearly Defined
4. Goals, Scope, Expectation, Measures Must Be Clearly Defined
5. Must Be Done Consistently

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• Sample Recommendations from a Best Practice Assessment
1. Define, Recognize and Deploy the
Data Governance Operating Model of Roles & Responsibilities
2. Create, Deliver and Act on a Data Governance Communications Plan
3. Organize, Staff and Deploy the Data Governance Team
4. Incrementally Roll Out the Data Governance Practice Into Business Areas by
Concisely Defining / Formalizing the Actions of Participants
5. Deliver a Data Governance Documentation Platform

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Get the Business to Tell You Where
DG will Add Value for the Business.
Demonstrating Value

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• Questions to Get the Business to Describe the Value Add:
 What can’t you do that you want to do because you don’t have the data to do it?
• What can’t you do …
• that you want to do …
• because you don’t have the data to do it …
Demonstrating Value

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1. What data / metadata do you use most often to achieve your objectives?
2. What is the primary source / system used by your area to obtain the data /
metadata? Who do go to get information about this source / system / data /
metadata?
3. What processes consume the data / metadata?
4. Do these processes have data / metadata challenges? If so, what are they?
5. What is the product or customer impact? How has this been tracked or
measured?
Demonstrating Value

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6. Is there an associated risk – brand, compliance, legal, etc?
7. What is the operational impact (e.g. money, FTEs, manual work-around, etc) of
the challenges? Have you tracked or quantified these impacts?
8. What other impacts should be noted?
9. Have you identified potential solutions? If so, what is the status of these
solutions – Scoped, Funded, Planned, In-Flight, etc?
10. What data / information is on your “wish list” that would better enable your
area to deliver on our Core Competencies?
Demonstrating Value

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Communicate DG Best Practice

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• When it Comes to Governing Your Data, It is Best Practice to Know …
– What data there is?
– Who defines, produces and uses that data?
– Who has decision making authority over the subject areas of data?
– What systems do the data resides in?
– Who in business has responsibility for that data?
– Who in IT has responsibility for that data?
– Who “owns” the data?
– Where does the data flow?

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• Communicate Best Practice with Roles
– Accountability for Communications
– Data Governance Team Leader
– Communications Partner
• Follow a Communications Plan
– Orientation Communications
– On-Boarding Communications
– On-Going Communications

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• “Active” Data Governance
– Pro-Active – Through Method / Process
– Re-Active – Through Issue Resolution
• Overlay Roles & Responsibilities Over Existing
Methodology & Work-Flow
• Data Stewardship Conflict Resolution Paths
Best Practice into Daily Operations

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• System Development Life Cycle (SDLC)
Application Development Life Cycle (ADLC)
Data Development Methodology (DDM)
DB Development Methodology (DbDM)
– Planning (Roles, Time Commitments, Tasks)
– Requirements
– Analysis
– Design
– Development
– Testing
– Implementation
– Maintenance
– Enhancement

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DATA DEFINER
DATA
PRODUCER
DATA STEWARD
COORDINATOR
DATA GOVERNANCE ACTIVITY MATRIX©
MASTER DATA
DEVELOPMENT
LIFE CYCLE
(MDDLC)
INFORMATION
GATHERING
(DOMAIN, SYSTEM,
STEWARDS)
OPERATIONAL DATA STEWARDS
DATA USER
DATA DOMAIN
STEWARD
(or designee)
DATA DOMAIN / LOB/FUNCTIONAL AREA
ASSESSMENT &
REQUIREMENTS
PLANNING &
ANALYSIS
SOLUTION DESIGN
SOLUTION
DEVELOPMENT
SOLUTION TESTING
SOLUTION
IMPLEMENTATION
SOLUTION
MONITORING &
MAINTENANCE
Activity initiated re: this domain,
Data Domain Steward is involved
in identifying and recording info
related Domains, Systems,
Stewards per issue or task.
Activity initiated re: this domain,
Steward Coordinator is involved in
identifying Operational Stewards
in this LOB/FA that should
participate in this work flow.
Assure appropriate business
meta-data is recorded.
Propose alternatives
for data definition
solution that best fits
with defined
requirements.
Provide input to the
development of the
data production
solution.
Provide definition
requirements &
gathering document.
Define data needed to
operate business &
report results.
Test data solution
from a definition
perspective. Assure
that appropriate
business meta-data is
recorded.
Produce user
requirements. Use
data needed to
operate business &
report results.
Coordinate activities of
Operational Stewards including
project timelines, status reporting,
tactical decision making. Assure
appropriate business meta-data is
recorded.
Provide data
definition guidance to
build the appropriate
solution.
Provide data usage
guidance to build the
appropriate solution.
Coordinate tasks associated
conducting planning and analysis
steps.
for data production
that best fits with the
data definition
solution and defined
requirements.
for data usage
solution that best fits
with defined
requirements.
Coordinate tasks associated
conducting planning and analysis
steps. Accept or Resolve solution
from the Steward Coordinator.
Coordinate activities of all
individuals related to development
work including timelines, status,
tactical decision making.
SYSTEM SMEs
IT
DATA SMEs
Test data solution
from a production
perspective. Assure
that appropriate
recorded.
Test data solution
from a usage
perspective. Assure
that appropriate
recorded.
Coordinate activities of the
Operational Stewards related to
testing work including timelines,
status, tactical decision making.
solution implementation including
timelines, status, tactical decision
making.
solution monitoring &
maintenance including timelines,
status, tactical decision making.
Perform EIS system testing.
Assure that appropriate technical
meta-data is recorded.
Perform EIS data testing. Assure
that appropriate technical meta-
data is recorded.
Coordinate and manage all
technical aspects of data solution
development. Assure that
appropriate technical meta-data is
recorded.
technical aspects of system
solution development. Assure
that appropriate technical meta-
data is recorded.
Coordinate system design with
Data Domain Stewards and
Steward Coordinators.
Coordinate data design with Data
Domain Stewards and Steward
Coordinators.
planning and analysis with Data
Coordinators.
technical aspects of data planning
and analysis with Data Domain
Stewards and Steward
Coordinators.
assessment & requirements
gathering with Data Domain
Coordinators.
technical aspects of data
assessment & requirements
gathering with Data Domain
Coordinators.
technical aspects of data
information gathering with Data
Coordinators. Assure appropriate
technical meta-data is recorded.
information gathering with Data
Coordinators. Assure appropriate
technical meta-data is recorded.
Participate in data
definition information
gathering as needed.
Participate in data
production
information gathering
as needed.
Participate in data
usage information
gathering as needed.
solution implementation.
solution monitoring &
maintenance.
implementation.
monitoring & maintenance.
Coordinate business tasks
associated with solution testing
steps.
associated with solution
implementation.
associated with solution
monitoring & maintenance.
As part of daily job,
identify operation
data issues pertaining
to their domain of
data.
identify operation
to their domain of
data.
identify operation
to their domain of
data.

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• Data Quality Methodology
– Qualify & Prioritize Data Issue
– Identify Affected Data Domain
– Identify Affected Data Stewards
– Conduct Data Systems & Data Resource Discovery
– Conduct Root Cause Analysis
– Conduct Cost-Benefit Analysis
– Analyze & Recommend Resolution
– Gain Approval, Funding, Resources
– Resolve Data Issue
• Cross Reference DQ Methodology & Resources
– Who does What and When?

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• Traditional Data Governance:
– Command-and-Control
– Responsibility Assigned
– New Rules
– New Process
– Over-and-Above
Communicating BP in a Non-Threatening Way
• Non-Invasive Data Governance:
– Behavior-Driven
– Accountability Recognized
– Application of Existing Rules
– Application to Existing Process
– Part of the Job

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Wrap Up
• This webinar covered –
– Criteria for Data Governance Best Practice Development
– How to Assess against Best Practice to Build Program Success
– Examples of Industry Selected DG Best Practice
– How to Communicate DG Best Practice in a Non-Threatening Way
– How to Build DG Best Practice into Daily Operations
• Next Real-World Data Governance Webinar – 2pm EST
– May 19, 2016 – A Data Governance Framework for Smart Data w/Tony Sarris

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Wrap Up

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• Robert S. Seiner
KIK Consulting & Educational Services – KIKconsulting.com
The Data Administration Newsletter – TDAN.com
Post Office Box 112571, Upper St. Clair, Pennsylvania 15241
412.220.9643, 412.220.9644 (Fax)
rseiner@kikconsulting.com
rseiner@tdan.com
@RSeiner
@TDAN_com
#RWDG
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How to Implement Data Governance Best Practice

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