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Engineering Data Mesh in Azure Cloud

Engineering Data Mesh in Azure Cloud: Implement data mesh using Microsoft Azure's Cloud Adoption Framework

By Aniruddha Deswandikar
$39.99 $27.98
Book Mar 2024 314 pages 1st Edition
eBook
$39.99 $27.98
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eBook
$39.99 $27.98
Print
$49.99
Subscription
$15.99 Monthly

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Product Details


Publication date : Mar 29, 2024
Length 314 pages
Edition : 1st Edition
Language : English
ISBN-13 : 9781805120780
Category :
Concepts :
toc View table of contents toc Preview Book toc Download Code

Key benefits

  • 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

What do you get with eBook?

Feature icon Instant access to your Digital eBook purchase
Feature icon Download this book in EPUB and PDF formats
Feature icon Access this title in our online reader with advanced features
Feature icon DRM FREE - Read whenever, wherever and however you want
Buy Now

Product Details


Publication date : Mar 29, 2024
Length 314 pages
Edition : 1st Edition
Language : English
ISBN-13 : 9781805120780
Category :
Concepts :

Table of Contents

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

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