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

Product type Paperback

Published in Mar 2024

Publisher Packt

ISBN-13 9781805120780

Length 314 pages

Edition 1st Edition

Languages

Python

Tools

Azure

Concepts

Data Science

Author (1):

Aniruddha Deswandikar

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Table of Contents (23) Chapters

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

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Table of Contents (23) Chapters

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Table of Contents (23) Chapters

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