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

Product type Paperback

Published in Jun 2020

Publisher Packt

ISBN-13 9781838646677

Length 810 pages

Edition 1st Edition

Tools

Office 365

Concepts

Project Management

Authors (2):

Gaurav Mahajan

Sudeep Ghatak

View More author details

Table of Contents (19) Chapters

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

Summary

In this chapter, we had a deeper look at the Amazon Athena service, which is an AWS-managed version of Apache Presto. We looked at how to optimize our data and queries to increase query performance and reduce costs.

Then, we explored how Athena can be used as a SQL query engine – not only for data in an Amazon S3 data lake but also for external data sources such as other database systems, data warehouses, and even CloudWatch logs using Athena Query Federation.

Finally, we explored Athena Workgroups, which let us manage governance and costs. Workgroups can be used to enforce specific settings for different teams or projects, and can also be used to limit the amount of data that's scanned by queries.

In the next chapter, we will take a deeper dive into another Amazon tool for data consumers as we look at how we can create rich visualizations and dashboards using Amazon QuickSight.