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

SCDs

In data warehousing, an SCD is used to manage infrequent changes to the values of a business entity over time, as opposed to changes that occur on a set schedule. Star schema design theory defines various types of SCDs, with Type 1 and Type 2 being the most common. In practice, a dimension table may support a combination of SCD types, such as Type 3 and Type 6, for tracking historical changes. Understanding the differences between these SCD types can be useful for designing an effective data warehousing solution.

Type 1 SCD

A Type 1 SCD design approach updates the dimension table with the most recent changes every time updates in the sources are seen. This method is typically used for storing supplementary values such as email addresses or company names of customers. If a customer’s contact information is altered, an update will be made to the dimension table to reflect the changes. The key of the table, such as CustomerID, will remain unchanged, ensuring that links...