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Azure Data and AI Architect Handbook

You're reading from   Azure Data and AI Architect Handbook Adopt a structured approach to designing data and AI solutions at scale on Microsoft Azure

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Product type Paperback
Published in Jul 2023
Publisher Packt
ISBN-13 9781803234861
Length 284 pages
Edition 1st Edition
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Authors (2):
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Olivier Mertens Olivier Mertens
Author Profile Icon Olivier Mertens
Olivier Mertens
Breght Van Baelen Breght Van Baelen
Author Profile Icon Breght Van Baelen
Breght Van Baelen
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Toc

Table of Contents (18) Chapters Close

Preface 1. Part 1: Introduction to Azure Data Architect
2. Chapter 1: Introduction to Data Architectures FREE CHAPTER 3. Chapter 2: Preparing for Cloud Adoption 4. Part 2: Data Engineering on Azure
5. Chapter 3: Ingesting Data into the Cloud 6. Chapter 4: Transforming Data on Azure 7. Chapter 5: Storing Data for Consumption 8. Part 3: Data Warehousing and Analytics
9. Chapter 6: Data Warehousing 10. Chapter 7: The Semantic Layer 11. Chapter 8: Visualizing Data Using Power BI 12. Chapter 9: Advanced Analytics Using AI 13. Part 4: Data Security, Governance, and Compliance
14. Chapter 10: Enterprise-Level Data Governance and Compliance 15. Chapter 11: Introduction to Data Security 16. Index 17. Other Books You May Enjoy

Preface

With data quickly becoming an essential asset of any business, the need for cloud data and AI architects has never been higher. The Azure Data and AI Architect Handbook will assist any data professional or academic who is looking to advance their skill set in cloud data platform design. 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.

The book introduces core data architecture design concepts and Azure data and AI services. Cloud landing zones and best practices are explained to build up an enterprise-scale data platform from scratch. Next, you will get a deep dive into various data domains, such as data engineering, business intelligence, data science, and data governance. You’ll learn about various methods for ingesting data into the cloud, designing the right data warehousing solution, managing large-scale data transformations, extracting valuable insights, and how to leverage cloud computing and (generative) AI to drive advanced analytical workloads. Finally, you will discover how to add data governance, compliance, and security to a solution.

By the end of this book, you will have gained the necessary expertise to become a well-rounded Azure data and AI architect.

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