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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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Toc

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

Summary and key takeaways

This has been a lengthy chapter with a variety of findings, from applying the Pareto principle to maximizing outcomes and impact, and then forming your very own fine-tuned strategy when dealing with data and business challenges, improving the state of data in the enterprise, and shining with the ultimate data leadership skills.

Additionally, we reviewed a case study about forming a new business opportunity within the company while using existing data – something that probably deserves a separate book to really go into detail.

Takeaway #1 – using the Pareto principle as your compass

Let’s start with a few leading learnings that helped us succeed, adopt the Pareto approach, and eventually come up with our own methodology:

  • Emphasize teamwork in data management: Success hinges on a collaborative, skilled team committed to ongoing learning and achievement recognition
  • Implement effective change management: Essential for...
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