AWS Glue Data Catalog and Metastore for Data Engineers

Managing metadata is one of the most critical challenges in building a scalable, high-performing data lake. Without a centralized, organized catalog, your data assets quickly turn into an unmanageable data swamp. This course provides a clear, text-only pathway to mastering the AWS Glue Data Catalog and Metastore, helping you design structured, query-ready data architectures. You will transition from understanding basic metadata concepts to implementing secure, efficient, and highly organized data lakes. Through structured explanations and clear code examples, you will learn how to automate schema discovery, manage partitions, and integrate your catalog with powerful analytical engines. What you'll learn: - Understand the foundational role of metadata catalogs in modern cloud data lakes - Configure AWS Glue databases, tables, and partitions to organize your storage - Integrate the Glue Data Catalog with Athena, Redshift Spectrum, and EMR for seamless querying - Compare the AWS Glue Data Catalog with the traditional Apache Hive metastore to make informed architecture choices - Implement column-level data governance and access control using Lake Formation - Apply modern data cataloging best practices, including schema evolution and partition projection This course begins with core definitions and the fundamental role of metadata in the cloud. You will then progress through step-by-step written guides on catalog configuration, crawler setup, engine integration, and security policies. This course is designed for beginner data engineers, cloud architects, and database administrators who are new to AWS data lake governance. No prior experience with AWS Glue is required, though a basic understanding of SQL and cloud storage concepts is helpful. Start reading today to build a secure, organized, and query-optimized AWS data catalog.