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Data Governance Handbook

You're reading from   Data Governance Handbook A practical approach to building trust in data

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Product type Paperback
Published in May 2024
Publisher Packt
ISBN-13 9781803240725
Length 394 pages
Edition 1st Edition
Languages
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Author (1):
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Wendy S. Batchelder Wendy S. Batchelder
Author Profile Icon Wendy S. Batchelder
Wendy S. Batchelder
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Table of Contents (24) Chapters Close

Preface 1. Part 1:Designing the Path to Trusted Data
2. Chapter 1: What Is Data Governance? FREE CHAPTER 3. Chapter 2: How to Build a Coalition of Advocates 4. Chapter 3: Building a High-Performing Team 5. Chapter 4: Baseline Your Organization 6. Chapter 5: Defining Success and Aligning on Outcomes 7. Part 2:Data Governance Capabilities Deep Dive
8. Chapter 6: Metadata Management 9. Chapter 7: Technical Metadata and Data Lineage 10. Chapter 8: Data Quality 11. Chapter 9: Data Architecture 12. Chapter 10: Primary Data Management 13. Chapter 11: Data Operations 14. Part 3:Building Trust through Value-Based Delivery
15. Chapter 12: Launch Powerfully 16. Chapter 13: Delivering Quick Wins with Impact 17. Chapter 14: Data Automation for Impact and More Powerful Results 18. Chapter 15: Adoption That Drives Business Success 19. Chapter 16: Delivering Trusted Results with Outcomes That Matter 20. Part 4:Case Study
21. Chapter 17: Case Study – Financial Institution 22. Index 23. Other Books You May Enjoy

Low adoption is costly

Imagine this: your company spent millions of dollars deploying a wonderfully crafted, embedded data governance-by-design program, only to move on to the next project, and the benefits realized at go-live evaporate.

This happens. Every. Single. Day.

Everyone has good intentions. We build a great business case. We deliver the program. We drive adoption with initial teams, groups, or systems. But over time, that adoption atrophies. Let’s dig into a specific example that is easy to understand.

Amazing visualization

Imagine a scenario where your company, eager to realize the full power of your data, invests in best-in-class data visualization technology. After months of vendor selection, procurement, development, and deployment, the solution sits unused, with minimal visualizations being built, in favor of using our old favorite: spreadsheets.

In this scenario, the data team that advocated for and gained approval to implement the solution loses...

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