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Engineering Data Mesh in Azure Cloud

You're reading from   Engineering Data Mesh in Azure Cloud Implement data mesh using Microsoft Azure's Cloud Adoption Framework

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Product type Paperback
Published in Mar 2024
Publisher Packt
ISBN-13 9781805120780
Length 314 pages
Edition 1st Edition
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Author (1):
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Aniruddha Deswandikar Aniruddha Deswandikar
Author Profile Icon Aniruddha Deswandikar
Aniruddha Deswandikar
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Toc

Table of Contents (23) Chapters Close

Preface 1. Part 1: Rolling Out the Data Mesh in the Azure Cloud FREE CHAPTER
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

Summary

In this chapter, we looked at a possible architecture for building a lakehouse. We discussed all its layers and components, as well as some scenarios. It is important to note that this is just one of the possible architectures. You can build a similar architecture using Azure Synapse Analytics. But what we have presented here is a popular architecture that’s typically used by many companies.

The next three chapters are architecture references and will be in a very similar format as this chapter.

In the next chapter, we will look at big data processing using Azure Synapse Analytics.

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