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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

Metadata as a service

Metadata as a service needs to be designed into a platform to drive automation and enable data sharing, governance, and Data Integration. The collection of metadata needs to take place throughout the life cycle of data, across all data management functions such as the development and deployment of data, data ingestion, Data Integration, and data consumption until its end of life. Metadata collection at every stage of the data life cycle enables us to make intelligent decisions to increase business value. In the following section, we will dive into some important points about metadata collection.

Metadata collection

To enable data consumption and enforce the right level of Data Governance, data must be discoverable and understood. This starts by collecting metadata wrapped around data. Metadata should be leveraged to create a 360-degree view that represents everything there is to know about assets, whether data assets, data related assets, and Data Products...

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