You're reading from Data Engineering with AWS Learn how to design and build cloud-based data transformation pipelines using AWS

Product type Paperback

Published in Dec 2021

Publisher Packt

ISBN-13 9781800560413

Length 482 pages

Edition 1st Edition

Languages

Python

Tools

AWS

Concepts

Data Analysis

Author (1):

Gareth Eagar

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

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...