Book Image

Azure Data and AI Architect Handbook

By : Olivier Mertens, Breght Van Baelen
Book Image

Azure Data and AI Architect Handbook

By: Olivier Mertens, Breght Van Baelen

Overview of this book

With data’s growing importance in businesses, the need for cloud data and AI architects has never been higher. The Azure Data and AI Architect Handbook is designed to assist any data professional or academic looking to advance their cloud data platform designing skills. This book will help you understand all the individual components of an end-to-end data architecture and how to piece them together into a scalable and robust solution. You’ll begin by getting to grips with core data architecture design concepts and Azure Data & AI services, before exploring cloud landing zones and best practices for building up an enterprise-scale data platform from scratch. Next, you’ll take a deep dive into various data domains such as data engineering, business intelligence, data science, and data governance. As you advance, you’ll cover topics ranging from learning different methods of ingesting data into the cloud to designing the right data warehousing solution, managing large-scale data transformations, extracting valuable insights, and learning how to leverage cloud computing to drive advanced analytical workloads. Finally, you’ll discover how to add data governance, compliance, and security to solutions. By the end of this book, you’ll have gained the expertise needed to become a well-rounded Azure Data & AI architect.
Table of Contents (18 chapters)
1
Part 1: Introduction to Azure Data Architect
4
Part 2: Data Engineering on Azure
8
Part 3: Data Warehousing and Analytics
13
Part 4: Data Security, Governance, and Compliance

Summary

Data governance and compliance are critical components of any data strategy. In this chapter, we explored the importance of data governance, its goals, and the roles involved in its implementation, along with Microsoft Purview and data governance frameworks.

We highlighted four main goals of data governance, namely managing an ever-growing data landscape, overcoming data silos, increasing data agility, and complying with data regulations.

The chapter also discussed the different roles involved in data governance. Executives, governance boards, data stewards, data owners, and SMEs all have a part to play in ensuring that data is managed effectively and efficiently.

We explored Microsoft Purview as a core component for the implementation of data governance and compliance, which provides a Data Map, Data Catalog, and Data Estate Insights. This tool can help organizations understand their data landscape (even in its most decentralized form) and make better decisions about...