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

Product type Paperback

Published in May 2024

Publisher Packt

ISBN-13 9781803240725

Length 394 pages

Edition 1st Edition

Languages

Python

Concepts

Data Governance

Author (1):

Wendy S. Batchelder

View More author details

Table of Contents (24) Chapters

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

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Technical Metadata and Data Lineage

Establishing a high-value, high-return-on-investment (ROI) data lineage capability is a fundamental capability for any data governance program. The success or failure of a Chief Data & Analytics Officer hinges on being able to answer a few key core questions:

Where is my data?
Who owns it?
How is it classified?
Is the data safe and secure?
How does it change (or how was it changed) as it moves through the company?
Can I trust the data? Is it of high quality?

Data lineage is the ability to see the journey the data has taken across your organization. Data lineage captures the source of any transposition changes and the overall journey of where that data has come and gone. It provides a line of sight into how the data has evolved across its source, journey, and evolution.

Building on the Metadata Management capabilities outlined in Chapter 6, Metadata Management, this chapter will focus on the more technical...