Modern data platforms often require efficient pipelines to transform large volumes of raw data into optimized formats for analytics and reporting. AWS Glue is a serverless data integration service that simplifies building and managing ETL (extract, transform, load) workflows, especially when used with Amazon S3 as a central data lake.
In this Cloud Lab, you’ll learn to implement a batch ETL pipeline. You’ll start by exploring raw CSV data stored in Amazon S3. Then, you’ll use a Glue crawler to catalog this data and define its schema. You’ll create a Glue job that transforms the CSV data into Parquet format and partitions it based on a selected column for better organization and performance. You’ll also configure a scheduled trigger to run the ETL job daily without manual intervention.
By the end of this lab, you’ll be equipped to design and automate batch ETL pipelines using AWS Glue. These skills are essential for data engineers and developers working with large-scale data processing and building serverless data lake architectures. The architecture diagram shows the infrastructure you’ll build in this Cloud Lab:
