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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

Understanding the TOM – From strategy to operation

In the pursuit of effective data governance, the interconnected elements of people, processes, technology, and culture must be harmoniously aligned. This alignment is achieved through a well-defined TOM.

The implementation, execution, and assessment of the TOM is typically carried out by the organization’s data steering committee and chief data officer, with the aid of various stakeholders from different departments. This includes IT, operations, finance, and others who understand the organization’s strategic goals. However, among these, data stewards play a pivotal role in the success of the TOM.

In the context of the TOM, the role of a data steward can be broken down as follows:

  • Defining data processes: Data stewards outline the processes needed to manage data effectively. For instance, they can help design workflows for data collection, validation, storage, and analysis. This ensures that data...
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