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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

Fulfilling the business and data strategy – Where do you want to go?

If you were granted three wishes by a wizard for your data roadmap, what would you ask for?

To answer the question, you need to define what good looks like for your organization.

Now imagine you have to call the wizard via your stakeholders. Defining the good is the key to asking for the apt wishes from the wizard.

As you ask for the three wishes you have to convince your stakeholders that the three wishes are valid, measurable, and most importantly, relevant to the organization’s goals.

So, what does it mean to stakeholders when the three wishes become true?

The three requirements for a good data roadmap are as follows:

  • Formalized data standards integrated into modern engineering processes so that business users can trust the data with confidence. For example, during the data ingestion stage, an automated script could check whether incoming currency data adheres to the prescribed...
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