9781805128946_

Overcome data mesh adoption challenges using the cloud-scale analytics framework and make your data analytics landscape agile and efficient by using standard architecture patterns for diverse analytical workloads

Key Features

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

Book 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 and spend 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, youll focus on the Azure Cloud Adoption Framework 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 implementation and adoption of 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 section covers some common architecture patterns used for modern analytics frameworks like artificial intelligence (AI). By the end of this book, youll be able to transform existing analytics frameworks into a streamlined data mesh using MS Azure, thereby navigating challenges and implementing advanced architecture patterns for modern analytics workloads.

What you will learn

Build a strategy for implementing 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

Who this book is for

This book is for chief data officers and data architects of large and medium-size organizations who are struggling to maintain silos of data and analytics projects. Data architects and data engineers looking to understand data mesh and how it can help their organizations democratize data and analytics will also benefit from this book. Prior knowledge of managing centralized analytical systems, as well as experience with building data lakes, data warehouses, data pipelines, data integrations, and transformations is needed to get the most out of this book.

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Engineering Data Mesh in Azure Cloud

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