RWDG Webinar: Writing Data Governance Policies & Procedures

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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
Twitter About This Webinar at #RWDG
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Robert S. Seiner
KIK Consulting & Educational Services – KIKconsulting.com
The Data Administration Newsletter – TDAN.com
Real-World Data Governance
Writing Data Governance
Policies & Procedures
Monthly Webinar Series Hosted by Dataversity
February 18, 2016 – 2:00 p.m. EST

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Writing Data Governance P & P
Session Abstract
• A Data Governance Policy is a guide to making decisions and delivering rational
outcomes pertaining to the data of your organization.
• A Data Governance Program delivers a way to formally get to the outcomes.
• Writing policy and associated procedures properly can be paramount to success.
• This webinar will cover –
– Essential Components of a Data Governance Policy
– Crafting Basic Data Governance Policy Principles
– Verbiage and Diagrams to Build a Data Governance Policy
– Why Policy is Necessary for Your Program
– Process and Procedure to Support the Policy

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• What is the Purpose of a Policy?
Approved and Intended to
Influence and Determine
Decisions, Actions and Other Matters.
First Things First

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• What is the Purpose of a Data Governance Policy?
– Approved and intended to influence and determine decisions, actions, and other
matters associated with Data Governance.
– Spells out what Data Governance is
– Spells out why Data Governance is important and necessary
– Spells out that you have a Data Governance Program
– Spells out how Data Governance will work
– Spells out who has the responsibility for Data Governance
– Spells out who supports Data Governance
– Spells out when Data Governance will be applied
– Spells out how Data Governance will be enforced
First Things First

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• Do you require a Data Governance Policy? … YES!
– The Organization is Policy-Driven
– Demonstrates Senior Leadership Support
– Outlines Who is Responsible and Enforcement of Rules
First Things First

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• Do you require a Data Governance Policy? … NO!
– Organization is Not Policy-Driven
– Senior Leadership Demonstrates Support in Other Ways
– Guidelines Work Better / Enforce Rules Through Guidelines
– We already have policies in place for:
• Information Security
• Privacy
• Regulations & Compliance
• Data Protection / Classification
• Data Sharing
• Data Quality
– What will a Data Governance Policy add that these don’t address?
First Things First

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• Components of a Data Governance Policy
– Introduction
– Data Governance Policy Statement
– Data Governance Principles
– Data Governance Dimensions
Essential Components

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• Introduction
– Purpose
• The Data Governance Policy is designed to manage the creation,
transformation, and usage of data and related information owned
by or in the care of Company.
• Example purposes:
– This policy directs the development of common data
definitions, standards, requirements and processes.
– This policy directs the enforcement of data lines of authority.
– This policy assures that the Data Governance Policy Principles
defined in this document are fully implemented.

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• Introduction
– Scope
• This policy applies to all employees, contractors, temporary
employees, consultants, and authorized agents of the Company.
• Example scopes:
– This policy applies to all data that is managed as an internal
asset to Company.
– This policy applies to all Personally Identifiable Information
(PII) and Personal Health Information (PHI) handled by
employees and contractors of the Company.
– This policy applies all internally managed data excluding
Human Resource data that is not in scope for the Program.

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• Introduction
– Violations
• Data and information is a critical component of Company business.
• All users must maintain the quality and integrity of these resources.
• Violations of this policy may be considered serious breaches of
trust, which can result in disciplinary action up to and including
termination of employment or contract and prosecution in
accordance with applicable federal, state, and local laws.

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• Data Governance Policy Statement
– It is the policy of Company to require that all data defined, produced
and used by or in the care of Company be governed as a corporate asset
through defined data governance standards and procedures.

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• Data Governance Policy Statement
– This Data Governance Policy will be implemented to formalize how
people of the Company behave consistent with the defined Data
Governance Principles represented on “The Graphic”.

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Copyright © 2012 – Robert S. Seiner – KIK Consulting & Educational Services, LLC
Used by Permission Only
Data Governance Policy Principles

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• Data Governance Principles – How Data Governance Is Defined
1. Data is recognized as a valued and strategic enterprise asset.
2. Accountability for Data is clearly defined and enforced.
3. Data is managed to follow internal & external rules & regulations.
4. Data Quality is defined & managed consistently across the data lifecycle.
VERY IMPORTANT SLIDE

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• Principle 1
Data is recognized as a valued and strategic enterprise asset.
– Data can have a positive value or negative value.
– We all know the positive value data can have.
– How can data can negative value?
– Recognized meaning …
• The Definition of the asset must be governed.
• The Production of the asset must be governed.
• The Usage of asset must be governed.

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• Principle 2
Accountability for Data is clearly defined, recorded and enforced.
– Accountability is based on a person’s relationship to the data
– Relationships Include …
• Definer of Data
• Producer of Data
• User of Data
– Everybody is a Data Steward … Get Over It.
– Roles & Responsibilities clearly defined and enforced.

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• Principle 3
Data is managed to follow internal & external rules & regulations.
– This principle is not optional.
– Internal Data Management and Data Handling Rules
– “The Law” – External Regulatory & Compliance Rules
– Rules and regulations must be clearly …
• Documented
• Made Digest-able
• Communicated
• Enforced

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• Principle 4
Data Quality is defined & managed consistently across the data lifecycle.
– Part of Project Management no matter the Approach
• Waterfall Methodology
• Agile Methodology
• Reactive Issue Resolution
– All Phases of Data Management
• Data Definition
• Data Production
• Data Use

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• Data Governance Dimensions – How Data Governance Is Measured
• The following Data Governance Dimensions have been defined as a way to
measure the governance of data.
– Accessibility – Data accessibility will be defined and managed in
accordance with appropriate Business Rules for access and local and
Federal Rules and Regulations.
– Accuracy – Data should correctly reflect the real world object or an
event being described to enable informed decision-making at all levels.
– Completeness – All expected, mandatory attributes of data should be
provided.
– Consistency – Data across the Company should be in synch with the
system of record identified and used in all appropriate cases.

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• Data Governance Dimensions – How Data Governance Is Measured
• The following Data Governance Dimensions have been defined as a way to
measure the governance of data.
– Relevance (Non-Obsolete) – Data managed as an asset must be relevant
to the business and retired when obsolete.
– Timeliness – Data should be up-to-date, produced in a timely manner
and appropriate for the task at hand to support information needs.
– Uniqueness – Duplicate data should be avoided (or managed).

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• Messages for Management
– We are already governing data (but we are doing it informally).
DG Policy will help to formalize the governing of data.
– We can formalize how we govern data by putting
structure around what we are presently doing.
DG Policy will help to put structure around the governing of data.
Verbiage for Management

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• Messages for Management
– Policy May Be Necessary to Improve:
• How We Manage Data Risk & Secure/Protect Data
• Data Quality & Provide Quality Assurance
• Coordination, Cooperation, Communication Around Data

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• Messages for Management:
– 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.

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• What We Should Not 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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Diagrams to Support Data Governance Policy

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EXISTSNEW

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Procedures to Support Data Governance
• Data Governance Procedures
– Pet Peeve: Don’t call them Data Governance Procedures.
– Procedures that are Governed – Apply Governance to Procedures.
– Follow the Data Governance Bill of “Rights”.
– Pro-Active and Re-Active Data Governance.
– Use Governance Activity Matrix to Apply Governance to Process.

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• Govern Data Procedures
– Data Access Process
– Data Issue Resolution Process
– Data Definition / Data Modeling Process
– Data Production Process / Big Data Process
– Data Usage / Handling / Protection Process
– Project Management Involvement Process
• Waterfall Methodology
• Agile Methodology
– Data Retention / Elimination Process
– Data Quality Management Process
– Metadata Management Process
– Glossary, Dictionary and Data Change Management

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Data Dictionary
Business Metadata
Business Explanation of Data in Systems
Data
Systems, Databases, Reference (Code) Data, Technical Metadata
Vocabulary
Semantic Level
Terminology
Business Language We Use
MapstoHowUsed
Maps to
Multiple
Business Term
Standard Data Name
Business System
Data Name
Business System
Data Name
Business System
Data Name
System Data Name

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Completed
Add/Change Request Form
(artifact)
Requestor – Officers, Department Management, Directors
Requests will be validated and approved by Department Management prior to entering process.
Vocabulary Add / Change
Request Form
Includes Change Detail (artifact)
Data Governance Manager (DGM)
(role)
Return Request
To Complete Form
(process)
Vocabulary Standard
Semantic Business Glossary
(artifact)
Data Governance Steering Committee (DGSC)
(role)
Initiate Request
Through Request Process
(process)
Deliver
Vocabulary Change
(process)
Utilize
Steering Committee
(process)
Document Change in
Vocabulary
(process)
DataGovernanceMetadataPlatform
(artifact)
Document
(process)
Document
(process)
Document
(process)
Access to Metadata
(process)
Validate
Request
(process)
Validate / Approve
Request
(process)
Bi-Weekly Itemized
Change Requests & Status Report
(process)
Initiate Impact Assessment (can require use of additional process*)
Vocabulary Add / Change Process
Vocabulary Standard Analysis
Decision Point
Certify
Vocabulary Change
(process)
Requestor – Officers, Department Management, Directors
Access to Metadata
(process)
Should Add / Change to Vocabulary Be Considered?
Yes – Follow Vocabulary Rules / Guidelines,
Document Vocabulary Change & Complete Process
No – Document Change Request,
Initiate Vocabulary Request Denial Impact Assessment
* vocabulary, data dictionary, data processes

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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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Is a Policy Necessary for Your Program
• Evaluate Data Governance Policy Vs. Data Policy
• Leverage Existing Policies – Label Them Governance

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• Build a Collection of Data Governance Policies
• Build a Collection of Repeatable Procedures that will be Governed

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• Leverage Models and Matrices as Part of Policies
• Leverage Models and Matrices to Apply Governance to Processes

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Wrap Up
• Next Real-World Data Governance Webinar – 2pm EST
– March 17, 2016 – The Data Model as a Data Governance Artifact
• This webinar covered –
– Essential Components of a Data Governance Policy
– Crafting Basic Data Governance Policy Principles
– Verbiage and Diagrams to Build a Data Governance Policy
– Why Policy is Necessary for Your Program
– Process and Procedure to Support the Policy

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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
#RWDG
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RWDG Webinar: Writing Data Governance Policies & Procedures

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