This course will guide you through the key functionalities of this AWS service, from the basics to the most advanced ETL (Extract, Transform, Load) techniques. You’ll learn to create and manage Glue jobs, use Dynamic Frames for efficient data manipulation, and work with different Glue engines and features. We’ll explore how to integrate Glue with other AWS services like S3, Athena, and Redshift to build robust and scalable data pipelines.
We’ll cover topics such as using AWS Glue Studio for visual workflow development, security configuration, performance optimization, and troubleshooting common issues. EVERYTHING WILL BE HANDS-ON. Each video is a lab where you’ll learn to create and work with all the components of AWS Glue.
What you’ll learn:
- What AWS Glue is and how it works.
- Create and execute ETL jobs step by step.
- Create jobs with Glue Studio, using scripts and notebooks.
- Configure and use crawlers and the Data Catalog.
- Work with DataFrames and DynamicFrames in PySpark.
- Use multiple transformations for your jobs.
- Integrate with Amazon S3 and databases.
- Monitor logs and metrics with CloudWatch.
- Create triggers.
- Work with notebooks.
- Create workflows and pipelines.
- Work with the AWS CLI.
- Best practices and pipeline optimization.
