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Engineering Data Mesh In Azure Cloud Implement Data Mesh Using Microsoft Azures Cloud Adoption Framework 1st Edition Aniruddha Deswandikar

  • SKU: BELL-56406438
Engineering Data Mesh In Azure Cloud Implement Data Mesh Using Microsoft Azures Cloud Adoption Framework 1st Edition Aniruddha Deswandikar
$ 31.00 $ 45.00 (-31%)

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Engineering Data Mesh In Azure Cloud Implement Data Mesh Using Microsoft Azures Cloud Adoption Framework 1st Edition Aniruddha Deswandikar instant download after payment.

Publisher: Packt Publishing
File Extension: EPUB
File size: 17.87 MB
Pages: 400
Author: Aniruddha Deswandikar
ISBN: 9781805120780, 1805120786
Language: English
Year: 2024
Edition: 1

Product desciption

Engineering Data Mesh In Azure Cloud Implement Data Mesh Using Microsoft Azures Cloud Adoption Framework 1st Edition Aniruddha Deswandikar by Aniruddha Deswandikar 9781805120780, 1805120786 instant download after payment.

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.

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