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

Part 1: Rolling Out the Data Mesh in the Azure Cloud

Part 1 starts with the theory of the data mesh architecture as described by Zhamak Dehghani in her original whitepaper (https://www.thoughtworks.com/insights/whitepapers/the-data-mesh-shift) and maps it to Microsoft Azure’s Well-Architected Framework, Cloud Adoption Framework, and cloud-scale analytics framework. Crossing this chasm is difficult for companies. This section will make it easier to understand the theory and apply it to your Microsoft Azure-based analytical systems. Whether you already have an existing central analytical system that you wish to migrate to a data mesh architecture or you are building an analytical system from the ground up, this part of the book will help you pave the way forward to adopt the data mesh architecture on Microsoft Azure.

This part has the following chapters:

  • Chapter 1, Introducing Data Meshes
  • Chapter 2, Building a Data Mesh Strategy
  • Chapter 3, Deploying a Data Mesh Using the Azure Cloud-Scale Analytics Framework
  • Chapter 4, Building a Data Mesh Governance Framework Using Microsoft Azure Services
  • Chapter 5, Security Architecture for Data Meshes
  • Chapter 6, Automating Deployment through Azure Resource Manager and Azure DevOps
  • Chapter 7, Building a Self-Service Portal for Common Data Mesh Operations
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Engineering Data Mesh in Azure Cloud
Published in: Mar 2024 Publisher: Packt ISBN-13: 9781805120780
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