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Engineering Data Mesh in Azure Cloud

You're reading from  Engineering Data Mesh in Azure Cloud

Product type Book
Published in Mar 2024
Publisher Packt
ISBN-13 9781805120780
Pages 314 pages
Edition 1st Edition
Languages
Author (1):
Aniruddha Deswandikar Aniruddha Deswandikar
Profile icon Aniruddha Deswandikar

Table of Contents (23) Chapters

Preface 1. Part 1: Rolling Out the Data Mesh in the Azure Cloud
2. Chapter 1: Introducing Data Meshes 3. Chapter 2: Building a Data Mesh Strategy 4. Chapter 3: Deploying a Data Mesh Using the Azure Cloud-Scale Analytics Framework 5. Chapter 4: Building a Data Mesh Governance Framework Using Microsoft Azure Services 6. Chapter 5: Security Architecture for Data Meshes 7. Chapter 6: Automating Deployment through Azure Resource Manager and Azure DevOps 8. Chapter 7: Building a Self-Service Portal for Common Data Mesh Operations 9. Part 2: Practical Challenges of Implementing a Data Mesh
10. Chapter 8: How to Design, Build, and Manage Data Contracts 11. Chapter 9: Data Quality Management 12. Chapter 10: Master Data Management 13. Chapter 11: Monitoring and Data Observability 14. Chapter 12: Monitoring Data Mesh Costs and Building a Cross-Charging Model 15. Chapter 13: Understanding Data-Sharing Topologies in a Data Mesh 16. Part 3: Popular Data Product Architectures
17. Chapter 14: Advanced Analytics Using Azure Machine Learning, Databricks, and the Lakehouse Architecture 18. Chapter 15: Big Data Analytics Using Azure Synapse Analytics 19. Chapter 16: Event-Driven Analytics Using Azure Event Hubs, Azure Stream Analytics, and Azure Machine Learning 20. Chapter 17: AI Using Azure Cognitive Services and Azure OpenAI 21. Index 22. Other Books You May Enjoy

Building a Data Mesh Governance Framework Using Microsoft Azure Services

Distributed data and federated governance are key concepts of the data mesh. Data is dispersed across various domains or teams, allowing for scalability and agility. Federated governance ensures that each domain retains autonomy over its data while adhering to common principles and standards, driving collaboration and trust among the data product owners.

In the previous chapters, we looked at how to create a distributed network of data landing zones managed by a central data management zone. We saw how the data landing zone can be designed and built. As the mesh grows and more landing zones get added, the complexity of managing and maintaining these landing zones can grow exponentially. Having a solid, well-planned governance framework from the beginning will drastically reduce this management effort.

In this chapter, we will dive deeper into the governing aspects of the data mesh. We will cover both governance...

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