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Microsoft 365 and SharePoint Online Cookbook

You're reading from   Microsoft 365 and SharePoint Online Cookbook Over 100 practical recipes to help you get the most out of Office 365 and SharePoint Online

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Product type Paperback
Published in Jun 2020
Publisher Packt
ISBN-13 9781838646677
Length 810 pages
Edition 1st Edition
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Authors (2):
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Gaurav Mahajan Gaurav Mahajan
Author Profile Icon Gaurav Mahajan
Gaurav Mahajan
Sudeep Ghatak Sudeep Ghatak
Author Profile Icon Sudeep Ghatak
Sudeep Ghatak
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Toc

Table of Contents (19) Chapters Close

Preface 1. Section 1: AWS Data Engineering Concepts and Trends
2. Chapter 1: An Introduction to Data Engineering FREE CHAPTER 3. Chapter 2: Data Management Architectures for Analytics 4. Chapter 3: The AWS Data Engineer's Toolkit 5. Chapter 4: Data Cataloging, Security, and Governance 6. Section 2: Architecting and Implementing Data Lakes and Data Lake Houses
7. Chapter 5: Architecting Data Engineering Pipelines 8. Chapter 6: Ingesting Batch and Streaming Data 9. Chapter 7: Transforming Data to Optimize for Analytics 10. Chapter 8: Identifying and Enabling Data Consumers 11. Chapter 9: Loading Data into a Data Mart 12. Chapter 10: Orchestrating the Data Pipeline 13. Section 3: The Bigger Picture: Data Analytics, Data Visualization, and Machine Learning
14. Chapter 11: Ad Hoc Queries with Amazon Athena 15. Chapter 12: Visualizing Data with Amazon QuickSight 16. Chapter 13: Enabling Artificial Intelligence and Machine Learning 17. Chapter 14: Wrapping Up the First Part of Your Learning Journey 18. Other Books You May Enjoy

Federating the queries of external data sources with Amazon Athena Query Federation

As we've discussed several times in this book, Athena lets you query data that has been loaded into the data lake using standard SQL semantics. But since the launch of Athena, AWS has added additional functionality to enhance Athena to make it an even more powerful query engine.

One of those major enhancements, which became available in 2021 with Athena query engine v2, was the ability to run federated queries, which we will look at next.

Querying external data sources using Athena Federated Query

Query federation, also sometimes referred to as data virtualization, is the process of querying multiple external data sources, in different database engines or other systems, through a single SQL query statement. In November 2019, AWS announced the preview of Federated Query in Amazon Athena, which enables a single Athena query to query data in data lakes, as well as data from external sources...

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