Delve into core data mesh concepts and apply them to real-world situations
Safely reassess and redesign your framework for seamless data mesh integration
Conquer practical challenges, from domain organization to building data contracts
Purchase of the print or Kindle book includes a free PDF eBook
Description
Decentralizing data and centralizing governance are practical, scalable, and modern approaches to data analytics. However, implementing a data mesh can feel like changing the engine of a moving car. Most organizations struggle to start and get caught up in the concept of data domains, spending months trying to organize domains. This is where Engineering Data Mesh in Azure Cloud can help.
The book starts by assessing your existing framework before helping you architect a practical design. As you progress, you’ll focus on the Microsoft Cloud Adoption Framework for Azure and the cloud-scale analytics framework, which will help you quickly set up a landing zone for your data mesh in the cloud.
The book also resolves common challenges related to the adoption and implementation of a data mesh faced by real customers. It touches on the concepts of data contracts and helps you build practical data contracts that work for your organization. The last part of the book covers some common architecture patterns used for modern analytics frameworks such as artificial intelligence (AI).
By the end of this book, you’ll be able to transform existing analytics frameworks into a streamlined data mesh using Microsoft Azure, thereby navigating challenges and implementing advanced architecture patterns for modern analytics workloads.
What you will learn
Build a strategy to implement a data mesh in Azure Cloud
Plan your data mesh journey to build a collaborative analytics platform
Address challenges in designing, building, and managing data contracts
Get to grips with monitoring and governing a data mesh
Understand how to build a self-service portal for analytics
Design and implement a secure data mesh architecture
Resolve practical challenges related to data mesh adoption
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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.
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