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

Designing data pipelines on Azure

In the previous chapter, we discussed how ADF and Azure Synapse Analytics fit into a data architecture by providing data pipelines for batch ingestion.

Here, we will look at how Azure Data Factory and Azure Synapse Analytics are used for transformation pipelines. These pipelines will read data from one data lake tier, process it in some way, and write the resulting dataset to the next data lake tier.

Types of pipelines on Azure

Across all Azure services, we can find many different pipelines. However, we can classify these pipelines into three categories; data pipelines (also referred to as ETL or ELT pipelines), machine learning pipelines (also referred to as MLOps pipelines), and release pipelines (also referred to as CI/CD pipelines).

Data pipelines are used for data movements and data transformations, machine learning pipelines are used to (re)train and (re)deploy machine learning models, and release pipelines are used to push code through...