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

Understanding AI on Azure

Microsoft has a globally leading role in terms of cloud-based AI. This is all thanks to performant infrastructure, strategic partnerships, and heavy investment in machine learning services.

The AI offering on Azure can be classified into two distinct categories:

  • Pre-trained AI models
  • Workspace for data scientists and machine learning engineers

The first contains a range of ready-to-use and pre-trained AI models that can be quickly implemented (and combined), allowing for an innovative way to process unstructured data or enhance applications with machine learning features. The latter provides the environment for a data science team to create their own custom models and maintain them throughout their life cycle.

The pre-trained models are, presently, available in two services:

  • Azure Cognitive Services
  • Azure OpenAI Service

Azure Cognitive Services is a collection of models meant to mimic most human functionalities,...