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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

What is automation?

Automation broadly refers to the use of technology to perform tasks with minimal human intervention. It encompasses a wide range of techniques and technologies applied in various ways. The key aspects of automation include the following:

  • Reduced human involvement: The goal is to minimize the need for team members to manually perform tasks, leading to increased efficiency and productivity. A secondary benefit is team member satisfaction, which we will discuss later in this chapter.
  • Use of technology: Automation relies on various technologies, from simple tools and scripts to complex artificial intelligence (AI) algorithms.
  • Pre-defined instructions or processes: Automated tasks are typically guided by pre-programmed rules, instructions, or decision-making criteria. This could include primary data management algorithms, as defined in Chapter 10.

There are a number of types of automation beyond those covered in this chapter. For the purposes of...

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