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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

Product type Paperback

Published in Jul 2023

Publisher Packt

ISBN-13 9781803234861

Length 284 pages

Edition 1st Edition

Tools

Azure

Concepts

Data Science

Authors (2):

Olivier Mertens

Breght Van Baelen

View More author details

Table of Contents (18) Chapters

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

Why subscribe?

17. Other Books You May Enjoy

The Semantic Layer

Positioned after the data has been modeled in a data warehouse or lakehouse, the semantic layer acts as a performance-enhancing data querying layer for reporting, offering a more efficient and business-friendly view of the data. By employing aggregations, calculations, and business-oriented terms and concepts, the semantic layer simplifies the complexity of technical data structures and caters to the needs of business users. The end result is a well-defined data model that effectively translates the underlying data structures of the warehouse or lakehouse into business-oriented terms. The value of this is to allow reports to more quickly query and visualize data, as well as allow business people to understand the data structures and extract insights from them.

In this chapter, we’re going to cover the following main topics:

Multidimensional versus tabular models
The VertiPaq engine for tabular models
Modes in tabular models
Tools for...

The rest of the chapter is locked

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Authors (2)

Olivier Mertens

Olivier Mertens

Olivier Mertens is a cloud solution architect for Azure data and AI at Microsoft, based in Dublin, Ireland. In this role, he assisted organizations in designing their enterprise-scale data platforms and analytical workloads. Next to his role as an architect, Olivier leads the technical AI expertise for Microsoft EMEA in the corporate market. This includes leading knowledge sharing and internal upskilling, as well as solving highly complex or strategic customer AI cases. Before his time at Microsoft, he worked as a data scientist at a Microsoft partner in Belgium. Olivier is a lecturer for generative AI and AI solution architectures, a keynote speaker for AI, and holds a master's degree in information management, a postgraduate degree as an AI business architect, and a bachelor's degree in business management.

See other products by Olivier Mertens

Breght Van Baelen

Breght Van Baelen

Breght Van Baelen is a Microsoft employee based in Dublin, Ireland, and works as a cloud solution architect for the data and AI pillar in Azure. He provides guidance to organizations building large-scale analytical platforms and data solutions. In addition, Breght was chosen as an advanced cloud expert for Power BI and is responsible for providing technical expertise in Europe, the Middle East, and Africa. Before his time at Microsoft, he worked as a data consultant at Microsoft Gold Partners in Belgium. Breght led a team of eight data and AI consultants as a data science lead. Breght holds a master's degree in computer science from KU Leuven, specializing in AI. He also holds a bachelor's degree in computer science from the University of Hasselt.

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