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

ADLS for raw data ingestion

Before diving deeper into ingestion architectures, we need to introduce the fundamentals of data lakes, where the ingested data will land in the majority of cases.

A data lake can be seen as a mass storage with support for all kinds of data. It does not enforce specific file types or data types, which makes it a remarkably good landing zone for ingestion. The more rules that are enforced—as is the case in structured databases, for example—the likelier it becomes that data ingestion pipelines will break if the file type or schema changes.

On the Azure cloud, a data lake is a specific version of the Azure Storage account. Therefore, we will first introduce this service and its features.

Azure storage accounts

Azure storage accounts can be used to store all kinds of data objects. They provide four distinct types of storage, as follows:

  • Binary Large Object (Blob) storage
  • File storage
  • Queue storage
  • Table storage
  • ...