AWS ETL Data Pipeline - AWS Lambda, Redshift, S3, Event Bridge

I've created an AWS Lambda function that handles an ETL (Extract, Transform, Load) process. This function is responsible for extracting data from an API, applying necessary transformations, and then loading the processed data into a Redshift Data Warehouse. To automate this process, we've set up a scheduling mechanism using AWS EventBridge.

Explanation:

AWS Lambda Function: This is a serverless compute service in AWS used to run code without having to manage servers. In this context, it's used for the ETL process.

ETL (Extract, Transform, Load): ETL is a common data integration process. In this case, it involves three steps:

Extract: Gathering data from an external source, in this case, an API.

Transform: Applying specific data manipulations or conversions as required.

Load: Storing the processed data in a data warehouse.

Redshift Data Warehouse: Amazon Redshift is a data warehousing service that allows for the storage and analysis of large datasets.

AWS EventBridge: This is a serverless event bus service in AWS that makes it easy to connect different applications together using events. In this context, it's used to schedule and trigger the Lambda function to run the ETL process at specific intervals or in response to specific events.

So, the entire process involves extracting data from an API, processing it, and storing it in a Redshift Data Warehouse, with automation provided by AWS EventBridge.