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Azure Data and AI Architect Handbook

Azure Data and AI Architect Handbook

By : Olivier Mertens, Breght Van Baelen
4.5 (13)
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Azure Data and AI Architect Handbook

Azure Data and AI Architect Handbook

4.5 (13)
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)
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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

Storing Data for Consumption

This chapter will explore the critical topic of early data orchestration and storage design. As companies gather increasingly massive amounts of data, it becomes more important to establish best practices for managing and storing that data efficiently.

We will begin by examining how to classify data as structured, semi-structured, or unstructured, and how to determine its use case. We will also determine how data will be used and the differences between ACID transactions and non-ACID transactions, SQL and NoSQL databases, and OLAP and OLTP systems. Additionally, we will focus on when to choose which storage service in Azure, such as Azure Cosmos DB, Azure SQL Database, or Azure Blob Storage, based on your data platform’s specific functional and technical requirements.

By the end of this chapter, you will have a firm grasp of the fundamental principles of data storage design, as well as the tools and techniques available for constructing a robust...

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