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Azure Data and AI Architect Handbook

Azure Data and AI Architect Handbook

By : Olivier Mertens, Breght Van Baelen
4.4 (14)
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Azure Data and AI Architect Handbook

Azure Data and AI Architect Handbook

4.4 (14)
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

Transforming Data on Azure

Azure offers a wide range of services for data processing. One of the key features of Azure is its ability to easily transform data from various sources into a format that is suitable for further analysis and reporting.

In this chapter, we will discuss the following:

  • Designing data pipelines on Azure
  • Transforming data on Azure
  • Data transformation architectures
  • Data transformations in data lake tiers
  • Operationalizing data pipelines on Azure

This chapter will introduce the various tools and services available on Azure for data transformation, including Azure Data Factory, (ADF) Azure Stream Analytics, and Azure Databricks. We will explore the core features and capabilities of each service, and show in which scenarios they work best. In line with the previous chapter, the focus will be put on both batch processing and real-time processing.

Next, we will look at some example architectures and provide a quick guide on how to...

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