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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

Approaches to data warehousing

There are two popular approaches to designing a data warehouse, namely the normalized approach by Bill Inmon and the dimensional approach by Ralph Kimball. In this section, we’ll explain the two different approaches further in detail.

Normalized approach by Bill Inmon

The first approach we would like to introduce is the normalized approach by Bill Inmon. Bill Inmon was one of the first people to define the term data warehousing and defined it as a “subject-oriented, nonvolatile, integrated, time-variant collection of data in support of management’s decisions.” This means a data warehouse focuses on subjects, such as products and customers, and stores historical data for an indefinite time.

The Inmon design approach constructs a logical model for each subject that includes all relevant attributes, relationships, dependencies, and affiliations. This logical model uses a normalized structure (3NF) to minimize data redundancy...

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