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Data Management Strategy at Microsoft

You're reading from   Data Management Strategy at Microsoft Best practices from a tech giant's decade-long data transformation journey

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Product type Paperback
Published in Jul 2024
Publisher Packt
ISBN-13 9781835469187
Length 270 pages
Edition 1st Edition
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Author (1):
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Aleksejs Plotnikovs Aleksejs Plotnikovs
Author Profile Icon Aleksejs Plotnikovs
Aleksejs Plotnikovs
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Table of Contents (19) Chapters Close

Preface 1. Part 1:Thinking Local, Acting Global FREE CHAPTER
2. Chapter 1: Where’s My Data and Who’s in Charge? 3. Chapter 2: We Make Data Business Ready 4. Chapter 3: Thousands to One – From Locally Siloed to Globally Centralized Processes 5. Chapter 4: “Reactive! Proactive? Predictive” 6. Part 2: Build Insights to Global Capabilities
7. Chapter 5: Mastering Your Data Domains and Business Ownership 8. Chapter 6: Navigating the Strategic Data Dilemma 9. Chapter 7: Unique Data IP Is Your Magic 10. Chapter 8: The Pareto Principle in Action 11. Part 3: Intelligent Future
12. Chapter 9: Data Mastering and MDM 13. Chapter 10: Data Mesh and Data Governance 14. Chapter 11: Data Assets or Data Products? 15. Chapter 12: Data Value, Literacy, and Culture 16. Chapter 13: Getting Ready for GenAI 17. Index 18. Other Books You May Enjoy

Data Governance = Data Excellence

Let’s dive into the topic of data governance, which is crucial for data teams. However, it’s quite common for data teams to struggle to showcase Data Governance as an enabler of insights to business teams. This is primarily due to the shift in Data Governance toward business ownership rather than remaining under the exclusive domain of the data team.

This shift, right from its onset, tends to create friction.

The prevailing perception within businesses is that Data Governance is only necessary for existing data issues. Thus, it’s often seen as a problem stemming from the data team’s failure to pre-emptively rectify data problems before they become a business need.

There’s some validity to this viewpoint. Ideally, in a world where data is always of high quality, complying with all policies and captured perfectly at the source, Data Governance would function more as a guide than an enforcer.

Governance is...

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