Mary Anne Hopper

Practitioner's Guide to Operationalizing Data Governance

• Gebundenes Buch

Produktbeschreibung

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 inreal-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.

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Produktdetails

• Wiley and SAS Business Series
• Verlag: Wiley / Wiley & Sons
• Artikelnr. des Verlages: 1W119851420
• 1. Auflage
• Seitenzahl: 240
• Erscheinungstermin: 9. Mai 2023
• Englisch
• Abmessung: 232mm x 164mm x 28mm
• Gewicht: 502g
• ISBN-13: 9781119851424
• ISBN-10: 1119851424
• Artikelnr.: 62798627

Autorenporträt

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.

Inhaltsangabe

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 Mat