Building an ETL Pipeline with Perl and Amazon Redshift

Creating an ETL pipeline that interacts with a data warehouse (e.g., Amazon Redshift, Google BigQuery, Snowflake, etc.) is a common use case in modern data engineering. In this blog post, we’ll walk through building an ETL pipeline in Perl that extracts data from a data warehouse, transforms it, and loads it into another data warehouse or database. For this example, we’ll use Amazon Redshift as the data warehouse.

Overview

This ETL pipeline will:

1. Extract: Fetch data from an Amazon Redshift data warehouse.
2. Transform: Perform transformations on the data (e.g., cleaning, aggregations, or calculations).
3. Load: Insert the transformed data into another Amazon Redshift table or a different data warehouse.

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