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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

Defining Primary Data Management

Primary Data Management is a core data governance capability, which brings together a core set of processes and technologies that are used to create a single unified view of specific types of data. This capability helps ensure that these specific and critical types of data have, above all else, consistency, accuracy, and accessibility enterprise-wide. Examples of Primary Data include: customer, product, vendor, and contact data. Because these types of data (customer, product, etc.) are often created in various departments across the organization, they require a special handling to unify and provision, so that the entire organization can have the same view of the data. Without Primary Data Management, companies struggle with consistency, accuracy and quality overall, which leads to poor customer experiences.

Example – Customer Experience

Imagine you are a customer of a large financial institution, and you open up a checking account at a...

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