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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

Why adoption matters – getting started

Driving the adoption of data governance solutions within a company requires a multi-faceted approach that addresses both the technical and human aspects of change, including employee responses to change, attitudes, and the overall organizational culture. There are some key, basics to start with as you frame out your adoption approach.

Start with the why

To bring people along on the journey to drive change, it’s best to start by explaining why change is required. What is or is not working well today that can benefit from the change? You should start by addressing three key areas when building your messaging:

  • Align data solutions with business goals: Clearly communicate how the solution will solve specific pain points, improve efficiency, or generate new opportunities. Use real-world examples and quantifiable metrics to demonstrate the value proposition.
  • Listen to feedback: Hear your stakeholders’ feedback...
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