Practitioner's guide to operationalizing data governance / Mary Anne Hopper.
By: Hopper, Mary Anne [author.]
Language: English Series: Wiley and SAS business series: Publisher: Hoboken, New Jersey : John Wiley & Sons, Inc., ©2023Description: 1 online resource (xiii, 226 pages) : illustrationsContent type: text Media type: computer Carrier type: online resourceISBN: 9781119851424; 9781119851462; 1119851467; 9781119851431; 1119851432; 1119851459; 9781119851455Subject(s): Database management | Management information systems -- Management | Data integrityAdditional physical formats: Print version:: Practitioner's guide to operationalizing data governanceDDC classification: 005.75/65 LOC classification: QA76.9.D3 | H6564 2023Online resources: Full text available at Wiley Online Library Click here to view| Item type | Current location | Home library | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|---|
EBOOK
|
COLLEGE LIBRARY | COLLEGE LIBRARY | 005.7565 H778 2023 (Browse shelf) | Available | CL-53718 |
Includes index.
Table of Contents
Acknowledgments xiii
Chapter 1 Introduction 1
Intended Audience 2
Experience 2
Common Challenge Themes 4
Chapter 2 Rethinking Data Governance 17
Results You Can Expect with Common Approaches to Data Governance 18
What Does Work 21
Rethinking Data Governance Summary 23
Chapter 3 Data Governance and Data Management 25
Results You Can Expect Focusing Purely on Data Governance or Data Management 26
SAS Data Management Framework 26
Aligning Data Governance and Data Management Outcomes 38
Misaligning Data Governance and Data Management 43
Data Governance and Data Management Summary 45
Chapter 4 Priorities 47
Results You Can Expect Using the Most Common Approaches to Prioritization 48
A Disciplined Approach to Priorities 50
Utilizing the Model 55
Priorities Summary 64
Chapter 5 Common Starting Points 65
Results You Can Expect with Too Many Entry Points 66
Building a Data Portfolio 66
Metadata 67
Data Quality 70
Data Profiling 75
Common Starting Points Summary 76
Chapter 6 Data Governance Planning 77
Results You Can Expect Without Planning 78
Defining Objectives 78
Defining Guiding Principles 85
Data Governance Planning Summary 88
Chapter 7 Organizational Framework 91
Results You Can Expect When There Is No Defined Organizational Structure 92
Organizational Framework Roles 92
Defining a Framework 94
Aligning the Model to Existing Structures 97
Aligning the Framework to the Culture 100
Simplifying the Model 103
Defining the Right Data Stewardship Model 104
Organizational Framework Summary 109
Chapter 8 Roles and Responsibilities 111
Results You Can Expect When Roles and
Responsibilities Are Not Clearly Defined 112
Aligning Actions and Decisions to Program Objectives 112
Using a RACI Model 119
Defining Roles and Responsibilities 126
Data Governance Steering Committee 126
Data Management 131
Naming Names 131
Roles and Responsibilities Summary 135
Chapter 9 Operating Procedures 137
Results You Can Expect Without Operating Procedures 138
Operating Procedures 138
Workflows 146
Operating Procedures Summary 152
Chapter 10 Communication 153
Results You Can Expect Without Communication 154
Communication Plan Components 154
Sample Communication Plan 156
Communication Summary 160
Chapter 11 Measurement 161
Results You Can Expect Without Measurement 162
What Measurements to Define 162
Program Scorecard – A Starting Point 166
Program Scorecard Sample 172
Measurement Summary 173
Chapter 12 Roadmap 175
Results You Can Expect Without a Roadmap 176
First Step in Defining a Roadmap:
Implementing Your Framework 176
Defining a Roadmap 178
Formality First or Save It for Later? 184
Critical Success Factors 185
Roadmap Summary 188
Chapter 13 Policies 189
Results You Can Expect Without Policies 190
Breaking Down a Policy 190
Contents of a Policy 192
Policy Example – Metadata 193
Policy Example – Data Quality 200
Policy Summary 204
Chapter 14 Data Governance Maturity 207
Results You Can Expect With Maturity 208
Data Governance Maturity Cycle 209
Maturing Your Program 215
Summary 216
About the Author 217
Glossary of Terms 219
Index 221
"Data Governance is an important topic for most organizations, yet they still are challenged in operationalizing and sustaining programs. The author shares her experience about what does and does not work in planning, designing, operationalizing, and (ultimately) sustaining a data governance program. It will explore where most organizations are challenged in program development and provide practical, actionable advice to help readers understand various pitfalls and a path forward"-- Provided by publisher.
About the Author
Mary Anne Hopper is a Senior Manager at SAS. She oversees the SAS Management and Advisory Consulting practice and has over 20 years’ experience helping clients develop and execute strategies in data governance, data management, reporting, and analytics. She is a co-author of the SAS Data Management Framework and the SAS Data Governance Maturity Model.
There are no comments for this item.