Preface

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL, without needing to manage any infrastructure.

This book begins with an overview of the serverless analytics experience offered by Athena and teaches you how to build and tune an S3 data lake using Athena, including how to structure your tables using open source file formats such as Parquet. You'll learn how to build, secure, and connect to a data lake with Athena and Lake Formation. Next, you'll cover key tasks such as ad hoc data analysis, working with ETL pipelines, monitoring and alerting KPI breaches using CloudWatch Metrics, running customizable connectors with AWS Lambda, and more. Moving ahead, you'll work through easy integrations, troubleshooting and tuning common Athena issues, and the most common reasons for query failure, as well as reviewing tips for diagnosing and correcting failing queries in your pursuit of operational excellence. Finally, you'll explore advanced concepts such as Athena Query Federation and Athena ML to generate powerful insights without needing to touch a single server.

By the end of this book, you'll be able to build and use a data lake with Amazon Athena to add data-driven features to your app and perform the kind of ad hoc data analysis that often precedes many of today's ML modeling exercises.