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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

Chapter 11: Ad Hoc Queries with Amazon Athena

In Chapter 8, Identifying and Enabling Varied Data Consumers, we explored a variety of data consumers. Now, we will start examining the AWS services that some of these different data consumers may want to use, starting with those that need to use SQL to run ad hoc queries on data in the data lake.

SQL syntax is widely used for querying data in a variety of databases, and it is a skill that is easy to find. As a result, there is significant demand from various data consumers for the ability to query data that is in the data lake using SQL, without having to first move the data into a dedicated traditional database.

Amazon Athena is a serverless, fully managed service that lets you use SQL to directly query data in the data lake, as well as query various other databases. It requires no setup, and the cost is based purely on the amount of data that is scanned to complete the query.

In this chapter, we will do a deep dive into Athena...

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