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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

Data Integration layer

The Data Integration layer of a Data Fabric architecture represents a set of capabilities in the form of services, tools, and data environments (development, test, and production) that support the development cycle of data to achieve downstream consumption. The Data Integration layer is composed of two pillars: data management and development workflow. Each pillar represents a group of capabilities and technologies that focus on realizing a phase in the life cycle of data. The end goal of the Data Integration layer is to technically support the ingestion, integration, and delivery of data. It needs to support the necessary provisioning and configuration to enable data to be consumed.

How does a Data Fabric support data assets, data-related assets, and Data Products?

Data can be a data asset or a data-related asset that can be grouped to represent one of the several assets in a Data Product. What differs between a data asset, a data-related asset, and a...

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