Preface

These days, organizations have gravitated toward data-driven business. Today, data integration across various data sources has become a key driver for businesses. In the cloud, data integration services such as AWS Glue do the undifferentiated heavy lifting based on serverless infrastructure. AWS Glue helps you to integrate data across different sources and build a data lake at scale in a serverless fashion without maintaining infrastructure.

This book shows you how AWS Glue can be used to solve real-world problems, along with teaching you about data processing, data integration, and building data lakes. It allows you to learn how to perform various aspects of data integration techniques such as data ingestion from various sources, data layout optimization, data and metadata management, and data pipeline management. Further, it covers data analysis use cases such as ad hoc queries, visualization, and real-time analysis using AWS Glue. Additional topics such as CI/CD, data quality validation, data sharing, and data security aspects, such as access control, encryption, auditing, and networking, are also covered. Toward the end, the book focuses on providing various monitoring options and the best practices for tuning, debugging, and troubleshooting.

The book takes you through the AWS Glue features such as jobs, the Data Catalog, crawlers, DataBrew, Glue Studio, custom connectors, and so on, in addition to AWS Lake Formation.

By the end of this book, you will be able to integrate data across different sources and build a data platform for scalable analysis using AWS Glue.