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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
Concepts
Author (1):
Aniruddha Deswandikar Aniruddha Deswandikar
Profile icon Aniruddha Deswandikar
LinkedIn
Aniruddha Deswandikar holds a Bachelor's degree in Computer Engineering and is a seasoned Solutions Architect with over 30 years of industry experience as a developer, architect and technology strategist. His experience spans from start-ups to dotcoms to large enterprises. He has spent 18 years at Microsoft helping Microsoft customers build their next generation Applications and Data Analytics platforms. His experience across Application, Data and AI has helped him provide holistic guidance to companies large and small. Currently he is helping global enterprises set up their Enterprise-scale Analytical system using the Data Mesh Architecture. He is a Subject Matter Expert on Data Mesh in Microsoft and is currently helping multiple Microsoft Global Customers implement the Data Mesh architecture.
See other products by 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

Architecture

While there are many architecture possibilities, it will always be divided into four buckets: ingest, store, process, and server. The components inside these buckets can change based on individual preferences. Components are often chosen based on the team’s skills – for example, a team that has experts in Databricks might prefer to use it for ingestion. Figure 14.1 shows one possible architecture for this workload:

Figure 14.1 – Advanced analytics with Databricks and Azure Machine Learning

Figure 14.1 – Advanced analytics with Databricks and Azure Machine Learning

Take a moment to study this architecture diagram; then, move on to the next section to learn more about the components involved and their functionality.

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Authors (1)

Profile icon Aniruddha Deswandikar
LinkedIn
Aniruddha Deswandikar holds a Bachelor's degree in Computer Engineering and is a seasoned Solutions Architect with over 30 years of industry experience as a developer, architect and technology strategist. His experience spans from start-ups to dotcoms to large enterprises. He has spent 18 years at Microsoft helping Microsoft customers build their next generation Applications and Data Analytics platforms. His experience across Application, Data and AI has helped him provide holistic guidance to companies large and small. Currently he is helping global enterprises set up their Enterprise-scale Analytical system using the Data Mesh Architecture. He is a Subject Matter Expert on Data Mesh in Microsoft and is currently helping multiple Microsoft Global Customers implement the Data Mesh architecture.
Read more
See other products by Aniruddha Deswandikar

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