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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
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Sonia Mezzetta
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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

Designing Data Integration and Self-Service

Data Integration and Self-Service represent two sides of the same coin in a Data Fabric architecture. Data Integration handles the technical development and processing of data, while Self-Service democratizes data. A DataOps framework overlays Data Integration and Self-Service to achieve the development and delivery of data with high productivity, speed, and quality control. A Data Fabric architecture comprises both the Data Integration and Self-Service layers and relies on the Data Governance layer for embedded and automated governance.

In this chapter, we’ll introduce you to the Data Integration and Self-Service layers of a Data Fabric architecture. We will discuss how these two layers interact with one another and how they work with the Data Governance layer to create a Data Fabric. The applicability of Data Fabric and DataOps principles will be discussed as part of the life cycle of data. We will conclude the chapter by presenting...

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