Hello and welcome to this learning path, which is going to 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. 

Before we begin - I’d like to introduce myself. My name is Alana Layton, and I am an AWS Content Creator here at Cloud Academy. Feel free to connect with me to ask any questions using the details shown on the screen. Alternatively, you can always get in touch with us here at Cloud Academy by sending an e-mail to support@cloudacademy.com where one of our cloud experts will reply to your question. 

This course has been created for those who are working with data pipelines on AWS within their organizations. If you are a data engineer or data analyst who’d like more information on how to transform their data using AWS tools and services, this course is for you. 

In this guided learning path, you will progress through a mixture of on-demand courses and hands-on labs, enabling you to feel comfortable working with Amazon EMR and AWS Glue. 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

• 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 fundamental knowledge of Python. 

Feedback on our courses here at Cloud Academy is valuable to both us as trainers and any students looking to take the same course in the future. If you have any feedback, positive or negative, it would be greatly appreciated if you could contact support@cloudacademy.com.

Please note that, at the time of writing this content, all course information was accurate.  AWS implements hundreds of updates every month as part of its ongoing drive to innovate and enhance its services. As a result, minor discrepancies may appear in the course content over time.  Here at Cloud Academy, we strive to keep our content up to date in order to provide the best training available. 

So, if you notice any information that is outdated, please contact support@cloudacademy.com.  This will allow us to update the course during its next release cycle. Thank you!