Understanding ETL Services on AWS
This learning path will explain two vital extract, transform, and load or ETL services on AWS. The two services this learning path will cover are AWS Glue and Amazon EMR.
The learning path starts with an overview of each of the services, including a hands-on lab for each service, as a result, you will learn:
- Serverless ETL
- The knowledge and architecture of a typical ETL project
- The prerequisite setup of AWS parts to use AWS Glue for ETL
- Knowledge of how to use AWS Glue to perform serverless ETL
- How to edit ETL processes created from AWS Glue
- The different ways to author an ETL job, such as Glue ETL Visual Authoring, Glue Studio Notebooks, Glue ETL Scripts, and Glue Interactive Sessions
- What AWS Glue Data Quality is, and its benefits
- The sensitive data detection feature and how it's used
- Encryption options with AWS Glue
- A foundational understanding of Amazon EMR
- Core Amazon EMR characteristics
- The EMR base architecture
- How AWS Glue compares to Amazon EMR
- How to make ETL processes more automated and repeatable using orchestration services such as AWS Data Pipeline, AWS Glue Workflows, and AWS Step Functions
- Knowledge of the AWS Data Wrangler library and how it provides an abstraction for extract, and load operations on AWS services
To get the most out of this course, you should have basic knowledge of the AWS platform. It also helps to have some familiarity with some of the core data storage destinations offered by AWS, such as Amazon S3. It will also help to understand the basics of serverless computing, and a fundamental knowledge of Python.
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Alana Layton is an experienced technical trainer, technical content developer, and cloud engineer living out of Seattle, Washington. Her career has included teaching about AWS all over the world, creating AWS content that is fun, and working in consulting. She currently holds six AWS certifications. Outside of Cloud Academy, you can find her testing her knowledge in bar trivia, reading, or training for a marathon.