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Principles of Data Fabric

You're reading from   Principles of Data Fabric Become a data-driven organization by implementing Data Fabric solutions efficiently

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Product type Paperback
Published in Apr 2023
Publisher Packt
ISBN-13 9781804615225
Length 188 pages
Edition 1st Edition
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Authors (2):
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DR. Tommy Dang DR. Tommy Dang
Author Profile Icon DR. Tommy Dang
DR. Tommy Dang
Sonia Mezzetta Sonia Mezzetta
Author Profile Icon Sonia Mezzetta
Sonia Mezzetta
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Toc

Table of Contents (16) Chapters Close

Preface 1. Part 1: The Building Blocks
2. Chapter 1: Introducing Data Fabric FREE CHAPTER 3. Chapter 2: Show Me the Business Value 4. Part 2: Complementary Data Management Approaches and Strategies
5. Chapter 3: Choosing between Data Fabric and Data Mesh 6. Chapter 4: Introducing DataOps 7. Chapter 5: Building a Data Strategy 8. Part 3: Designing and Realizing Data Fabric Architecture
9. Chapter 6: Designing a Data Fabric Architecture 10. Chapter 7: Designing Data Governance 11. Chapter 8: Designing Data Integration and Self-Service 12. Chapter 9: Realizing a Data Fabric Technical Architecture 13. Chapter 10: Industry Best Practices 14. Index 15. Other Books You May Enjoy

Data Fabric reference architecture

We have introduced and reviewed the design of three layers in a Data Fabric architecture. This establishes a Data Fabric reference architecture that could be leveraged as an approach in a digital transformation journey. It can also serve as a reference to build a roadmap on what, when, and how you can progress toward the building or buying of solutions to build a Data Fabric architecture.

Data Fabric architecture highlights

Let’s briefly highlight key points in each of the three layers of a Data Fabric architecture.

Data Governance layer

This represents the checks and balances of a Data Fabric architecture. It contains the brain (Metadata Knowledge Graph) that powers the body (Data Integration and Self-Service layers) to support the development and delivery of data that is quality controlled, trusted, and enforced. The Data Governance layer heavily relies on a sophisticated, active metadata- and event-driven approach. It applies...

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