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by Anthony Virtuoso (Author), Mert Turkay Hocanin (Author), Aaron Wishnick (Author)
Get more from your data with Amazon Athena's ease-of-use, interactive performance, and pay-per-query pricing
Key Features:
- Explore the promising capabilities of Amazon Athena and Athena's Query Federation SDK
- Use Athena to prepare data for common machine learning activities
- Cover best practices for setting up connectivity between your application and Athena and security considerations
Book Description:
Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using 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 like 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 on, you'll work through easy integrations, troubleshooting and tuning common Athena issues, and the most common reasons for query failure. You will also review tips to help diagnose and correct 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.
What You Will Learn:
- Secure and manage the cost of querying your data
- Use Athena ML and User Defined Functions (UDFs) to add advanced features to your reports
- Write your own Athena Connector to integrate with a custom data source
- Discover your datasets on S3 using AWS Glue Crawlers
- Integrate Amazon Athena into your applications
- Setup Identity and Access Management (IAM) policies to limit access to tables and databases in Glue Data Catalog
- Add an Amazon SageMaker Notebook to your Athena queries
- Get to grips with using Athena for ETL pipelines
Who this book is for:
Business intelligence (BI) analysts, application developers, and system administrators who are looking to generate insights from an ever-growing sea of data while controlling costs and limiting operational burden, will find this book helpful. Basic SQL knowledge is expected to make the most out of this book.
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