AWS data Engineering (https://aws.amazon.com/certification/certified-data-engineer-associate/)
- Data Engineering fundamentals
- Data Analytics and Visualization Fundamentals
- AWS Basic Introduction
- Redshift Database (https://docs.aws.amazon.com/redshift/latest/mgmt/welcome.html)
- Redshift SQL
- AWS Athena (https://docs.aws.amazon.com/athena/latest/ug/what-is.html)
- AWS Glue (https://docs.aws.amazon.com/glue/latest/dg/what-is-glue.html)
- Apache Kafka/Airflow (https://kafka.apache.org/) (https://airflow.apache.org/)
- AWS Quick sights (https://shorturl.at/QRS29)
- Intro to AWS Data Warehouses, Data Marts, Data Lakes, and ETL/ELT pipelines
- Configuring the AWS Command Line Interface tool
- Creating an S3 bucket
- Working with Databases and various File formats (Data Lakes)
- Amazon Database Migration Service (DMS) for ingesting data
- Amazon Kinesis and Amazon MSK for streaming data
- AWS Lambda for transforming data
- AWS Glue for orchestrating big data pipelines
- Consuming data – Amazon Redshift & Amazon Athena for SQL queries
- Amazon QuickSight for visualizing data
- Hands-on – AWS Lambda function when a new file arrives in an S3 bucket