Practitioner's Guide to Operationalizing Data Governance

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Discover what does―and doesn’t―work when designing and building a data governance program

In A Practitioner’s Guide to Operationalizing Data Governance, veteran SAS and data management expert Mary Anne Hopper walks readers through the planning, design, operationalization, and maintenance of an effective data governance program. She explores the most common challenges organizations face during and after program development and offers sound, hands-on advice to meet tackle those problems head-on.

Ideal for companies trying to resolve a wide variety of issues around data governance, this book:

  • Offers a straightforward starting point for companies just beginning to think about data governance
  • Provides solutions when company employees and leaders don’t―for whatever reason―trust the data the company has
  • Suggests proven strategies for getting a data governance program that’s gone off the rails back on track

Complete with visual examples based in real-world case studies, A Practitioner’s Guide to Operationalizing Data Governance will earn a place in the libraries of information technology executives and managers, data professionals, and project managers seeking a one-stop resource to help them deliver practical data governance solutions.

Author(s): Mary Anne Hopper
Series: Wiley and SAS Business Series
Publisher: Wiley
Year: 2023

Language: English
Pages: 241
City: Hoboken

Cover
Title Page
Copyright Page
Contents
Acknowledgments
Chapter 1 Introduction
Intended Audience
Experience
Common Challenge Themes
Metadata
Access to Data
Trust in Data
Data Integration
Data Ownership
Reporting/Analytics
Data Architecture
Reliance on Individual Knowledge
Culture
How Data Governance Can Help
Metadata
Access to Data
Trust in Data
Data Integration
Data Ownership
Reporting/Analytics
Data Architecture
Reliance on Individual Knowledge
Culture
Chapter 1 - Introduction Summary
Chapter 2 - Rethinking Data Governance
Chapter 3 - Data Governance and Data Management
Chapter 4 - Priorities
Chapter 5 - Common Starting Points
Chapter 6 - Data Governance Planning
Chapter 7 - Organizational Framework
Chapter 8 - Roles and Responsibilities
Chapter 9 - Operating Procedures
Chapter 10 - Communication
Chapter 11 - Measurement
Chapter 12 - Roadmap
Chapter 13 - Policies
Chapter 14 - Data Governance Maturity
Chapter 2 Rethinking Data Governance
Results You Can Expect With Common Approaches to Data Governance
Here Comes Panera
Voluntelling
Misaligning Titles and Roles
Project Delivery
Tool Deployment
What Does Work
Adopting Consistent Definitions
Disciplined Approach to Program Planning, Design, and Execution
Rethinking Data Governance Summary
Chapter 3 Data Governance and Data Management
Results You Can Expect Focusing Purely on Data Governance or Data Management
SAS Data Management Framework
Data Governance
Data Management
Data Stewardship
Business Drivers
Solutions
Methods
Aligning Data Governance and Data Management Outcomes
Data Architecture
Data Administration
Data Quality
Data Security
Metadata
Reference and Master Data
Reporting and Analytics
Data Life Cycle
Misaligning Data Governance and Data Management
Data Governance and Data Management Summary
Chapter 4 Priorities
Results You Can Expect Using the Most Common Approaches to Prioritization
The List
Level
Volume
Lunch
Communication
Emergency
A Disciplined Approach to Priorities
Business Value
Achievability
Utilizing the Model
University – Formal Weighted Model
Retailer – A Different Approach
Priorities Summary
Chapter 5 Common Starting Points
Results You Can Expect With Too Many Entry Points
Building a Data Portfolio
Metadata
Metadata Categories
Business Metadata
Technical Metadata
Operational Metadata
Data Quality
Business Definition
Data Element
Data Record
Data Movement
Data Profiling
Common Starting Points Summary
Chapter 6 Data Governance Planning
Results You Can Expect Without Planning
Defining Objectives
Our Objectives
Defining Guiding Principles
Data Governance Planning Summary
Chapter 7 Organizational Framework
Results You Can Expect When There Is No Defined Organizational Structure
Organizational Framework Roles
Support
Oversight
Operations
Facilitation
Defining a Framework
Data Governance Steering Committee
Program Management
Data Owner
Working Group
Data Stewardship
Data Management
Aligning the Model to Existing Structures
Leadership Team
Data Manager Team
Domain Definitions — Student
Domain Definitions — Business Operations
Domain Definitions — External
Data Manager
Data Steward
Ad-Hoc Working Group
Data Governance Management
Technical Data Operations
Aligning the Framework to the Culture
Data Governance Steering Committee
Data Governance Sub-Committee
Data Governance Office
Data Steward
Simplifying the Model
Defining the Right Data Stewardship Model
Data Domain Model
Application Model
Project Model
Organizational Framework Summary
Chapter 8 Roles and Responsibilities
Results You Can Expect When Roles and Responsibilities Are Not Clearly Defined
Aligning Actions and Decisions to Program Objectives
Strategy & Alignment
Establish Data Governance Program
Data Governance Operations
Data Architecture
Metadata
Data Quality
Reference & Master Data
Using a RACI Model
Strategy & Alignment
Establish Data Governance Program
Data Governance Program Operations
Data Architecture
Metadata
Data Quality
Reference & Master Data
Defining Roles and Responsibilities
Data Governance Steering Committee
Program Management
Data Governance Council
Data Owner Team
Working Group
Data Stewardship
Data Management
Naming Names
Roles and Responsibilities Summary
Chapter 9 Operating Procedures
Results You Can Expect Without Operating Procedures
Operating Procedures
Data Governance Steering Committee
Data Governance Council
Data Owner
Data Steward Team
Working Group
Program Management Team
Data Management Team
A Simplified View of Operating Procedures
Workflows
Policy Development
Data Issue Intake
Compliance Monitoring
Prioritization
Operating Procedures Summary
Chapter 10 Communication
Results You Can Expect Without Communication
Communication Plan Components
Message
Objective
Author(s)
Audience
Frequency
Medium
Sample Communication Plan
Communication Summary
Chapter 11 Measurement
Results You Can Expect Without Measurement
What Measurements to Define
Program Scorecard – A Starting Point
Data Governance Participation
Data Governance Program Milestones
Policy Compliance
Program Scorecard Sample
Measurement Summary
Chapter 12 Roadmap
Results You Can Expect Without a Roadmap
First Step in Defining a Roadmap: Implementing Your Framework
Defining a Roadmap
Workstreams
Launch Data Governance
Data Warehouse Program Management
Data Architecture
Metadata
Data Quality
Data Management
Formality First or Save it For Later?
Critical Success Factors
Roadmap Summary
Chapter 13 Policies
Results You Can Expect Without Policies
Breaking Down a Policy
Policy
Procedure
Standard
Best Practice
Data Management
Contents of a Policy
Policy Example – Metadata
Name
Policy Purpose
Policy Objectives
Policy Statement
Attendant Procedures and Standards
Metadata Collection Standard Template
Scope/Affected Area(s)
Roles and Responsibilities
Compliance
Effective Date
Maintenance and Review
Policy Example – Data Quality
Policy Purpose
Policy Objectives
Policy Statement
Procedures
Standards
Scope/Affected Area(s)
Roles and Responsibilities
Policy Summary
Chapter 14 Data Governance Maturity
Results You Can Expect With Maturity
Data Governance Maturity Cycle
Stage 1 – Define Program
Stage 2 – Identify Challenges
Stage 3 – Develop Policy
Stage 4 – Policy Execution
Stage 5 – Monitor and Communicate
Maturing Your Program
Summary
About the Author
Glossary of Terms
Index
EULA