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Driving Data Quality with Data Contracts

You're reading from   Driving Data Quality with Data Contracts A comprehensive guide to building reliable, trusted, and effective data platforms

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Product type Paperback
Published in Jun 2023
Publisher Packt
ISBN-13 9781837635009
Length 206 pages
Edition 1st Edition
Languages
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Author (1):
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Andrew Jones Andrew Jones
Author Profile Icon Andrew Jones
Andrew Jones
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Table of Contents (16) Chapters Close

Preface 1. Part 1: Why Data Contracts?
2. Chapter 1: A Brief History of Data Platforms FREE CHAPTER 3. Chapter 2: Introducing Data Contracts 4. Part 2: Driving Data Culture Change with Data Contracts
5. Chapter 3: How to Get Adoption in Your Organization 6. Chapter 4: Bringing Data Consumers and Generators Closer Together 7. Chapter 5: Embedding Data Governance 8. Part 3: Designing and Implementing a Data Architecture Based on Data Contracts
9. Chapter 6: What Makes Up a Data Contract 10. Chapter 7: A Contract-Driven Data Architecture 11. Chapter 8: A Sample Implementation 12. Chapter 9: Implementing Data Contracts in Your Organization 13. Chapter 10: Data Contracts in Practice 14. Index 15. Other Books You May Enjoy

Data contracts and the data mesh

Data mesh was invented by Zhamak Dehghani in 2019 (https://martinfowler.com/articles/data-monolith-to-mesh.html) and is a design pattern for building a domain-oriented, decentralized data platform. It focuses not just on the technology, but also the social and cultural changes required to achieve this goal and solve many of the problems we discussed in Chapter 1, A Brief History of Data Platforms.

The pattern is described through four principles:

  • Domain ownership
  • Data as a product
  • Self-serve data platform
  • Federated computational governance

Let’s go through each principle in turn and discuss how they relate to data contracts.

Domain ownership

Data mesh proposes a domain-oriented approach to organizing the responsibility and ownership of the data, where this ownership is decentralized to the business domains closest to the data – ideally, the data generators. They are the ones who know most about the data...

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