![](https://play.vidyard.com/tKeVSooggNcLsjw2e8FLuX.jpg)
Broadcast Date: June 17, 2019
Level: 200
Every data lake initiative begins with setting up extract, transform, and load (ETL) processes where data is moved from various data sources into a central data repository. In this tech talk, we will show how you can use AWS Glue to build, automate, and manage ETL jobs in a scalable, serverless Apache Spark platform. See how to support Python shell jobs too, in addition to Spark jobs.
![](https://pages.awscloud.com/rs/112-TZM-766/images/learning-objective.png)
Learning Objectives
- Learn about building a data lake on AWS
- Discover how to create ETL processes using AWS Glue
- Understand how serverless Spark and Python jobs reduce costs
![](https://pages.awscloud.com/rs/112-TZM-766/images/who-attend.png)
Who Should Attend?
Analysts, Developers, Data Scientists, Data Engineers, DBAs
Speakers
- Raghu Prabhu, Sr. Business Development Manager, AWS
![](https://pages.awscloud.com/rs/112-TZM-766/images/speakers.png)
Learn More
To learn more about the services featured in this talk, please visit:
https://aws.amazon.com/glue
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