Book Image

Data Engineering with AWS

By : Gareth Eagar
Book Image

Data Engineering with AWS

By: Gareth Eagar

Overview of this book

Written by a Senior Data Architect with over twenty-five years of experience in the business, Data Engineering for AWS is a book whose sole aim is to make you proficient in using the AWS ecosystem. Using a thorough and hands-on approach to data, this book will give aspiring and new data engineers a solid theoretical and practical foundation to succeed with AWS. As you progress, you’ll be taken through the services and the skills you need to architect and implement data pipelines on AWS. You'll begin by reviewing important data engineering concepts and some of the core AWS services that form a part of the data engineer's toolkit. You'll then architect a data pipeline, review raw data sources, transform the data, and learn how the transformed data is used by various data consumers. You’ll also learn about populating data marts and data warehouses along with how a data lakehouse fits into the picture. Later, you'll be introduced to AWS tools for analyzing data, including those for ad-hoc SQL queries and creating visualizations. In the final chapters, you'll understand how the power of machine learning and artificial intelligence can be used to draw new insights from data. By the end of this AWS book, you'll be able to carry out data engineering tasks and implement a data pipeline on AWS independently.
Table of Contents (19 chapters)
1
Section 1: AWS Data Engineering Concepts and Trends
6
Section 2: Architecting and Implementing Data Lakes and Data Lake Houses
13
Section 3: The Bigger Picture: Data Analytics, Data Visualization, and Machine Learning

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...