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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

Core capabilities

Data architecture needs to be more flexible and dynamic than ever before. Companies are evolving quickly, and the speed at which generative AI (GenAI) has emerged is a perfect example of the ever-changing needs of corporations. You will note that the capabilities presented next are not specifying which technologies you need to deploy. That is up to you and your stakeholders to decide. The following capabilities tell what you need to define as a part of your data architecture program.

Establishing a data architecture program

Ideally, data architects should report to your chief data and analytics office. In some organizations, you will see the data architecture function report to the chief architect; however, in most cases, this results in data architects being less intimately familiar with the objectives of the company’s data strategy and results in less data-friendly models. It can work well when your chief architect understands data complexities well...

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