From Data Extraction to Transformation: Creating an ELT Pipeline with Python

Extracting and transforming data is a crucial task in the field of data analytics and data science. The process of extracting data from various sources, transforming it to fit specific business requirements, and loading it into a data warehouse or data lake is commonly known as ETL (Extract, Transform, Load). However, in recent years, a new approach called ELT (Extract, Load, Transform) has emerged, which emphasizes loading data into a target data store before transforming it. In this tutorial, we will walk you through the process of creating an ELT pipeline using Python. The first step is to set up the development environment and install the required dependencies.