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Data Stewardship in Action

You're reading from   Data Stewardship in Action A roadmap to data value realization and measurable business outcomes

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Product type Paperback
Published in Feb 2024
Publisher
ISBN-13 9781837636594
Length 272 pages
Edition 1st Edition
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Author (1):
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Pui Shing Lee Pui Shing Lee
Author Profile Icon Pui Shing Lee
Pui Shing Lee
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Table of Contents (18) Chapters Close

Preface 1. Part 1:Why Data Stewardship and Why Me? FREE CHAPTER
2. Chapter 1: From Business Strategy to Data Strategy to Data Stewardship 3. Chapter 2: How Data Stewardship Can Help Your Organization 4. Chapter 3: Getting Started with the Data Stewardship Program 5. Part 2:How to Become a Data Steward and Shine!
6. Chapter 4: Developing a Comprehensive Data Management Strategy 7. Chapter 5: People, Process, and Technology 8. Chapter 6: Establishing a Data Governance Organization 9. Chapter 7: Data Steward Roles and Responsibilities 10. Chapter 8: Effective Data Stewardship 11. Chapter 9: Supercharge Data Governance and Stewardship with GPT 12. Part 3:What Makes Data Stewardship a Sustainable Success?
13. Chapter 10: Data Stewardship Best Practices 14. Chapter 11: Theory versus Real Life 15. Chapter 12: Case Studies 16. Index 17. Other Books You May Enjoy

Creating a data governance roadmap

Constructing a data governance roadmap is pivotal in establishing a data governance structure. This roadmap outlines the program’s objectives, implementation timeline, required resources, and progress monitoring plan. Here are some vital considerations when crafting a data governance roadmap:

  1. Define objectives: Begin by delineating clear goals for the data governance program. Aligning these with the organization’s overall strategy ensures a focus on achieving quantifiable results. For instance, an objective might be to enhance data quality by 20% in the first year.
  2. Identify stakeholders: Recognize those within the organization who have an interest in the data governance program. This could range from executives and IT staff to business users. For example, the marketing team might be stakeholders, as improved data quality can enhance their targeting efforts.
  3. Form a data governance team: This team oversees the data governance...
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