AWS Glue: Serverless ETL for Data Transformation

Data transformation is crucial for turning raw information into valuable insights. Discover how serverless technologies can simplify and scale your data processing workflows. This course provides a foundational understanding of serverless Extract, Transform, Load (ETL) principles, empowering you to build automated, cost-effective data pipelines using AWS Glue. You will gain the skills to prepare and standardize data for analytics and reporting. What you'll learn: Understand fundamental ETL concepts and the advantages of serverless data processing. Learn to configure Glue Crawlers for automated schema discovery and metadata management. Build and execute Glue ETL Jobs to transform data formats, such as CSV to Parquet. Apply partitioning and job bookmarks for optimized and resilient data processing. Manage and query metadata effectively using the Glue Data Catalog for data governance. Explore basic principles of defining Glue resources using infrastructure-as-code concepts. Implement strategies for cost-effective serverless ETL operations, including DPU right-sizing. The course begins with core ETL concepts and the architecture of AWS Glue, then guides you through setting up and running your first serverless data transformation jobs. You will progressively learn about data cataloging, job optimization techniques, and best practices for managing serverless ETL workflows. This course is designed for absolute beginners in cloud data engineering and those new to AWS Glue. No prior experience with cloud platforms or ETL tools is required. Start your journey into efficient, serverless data transformation today.