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Fastest way to implement an ETL pipeline
Table of contents
Introduction
In the world of data engineering, Extract, Transform, Load (ETL) pipelines are crucial for collecting, cleaning, and moving data from various sources to a target destination. ETL pipelines are also used to integrate different data sources and systems.
In this article, we will discuss how to implement an ETL pipeline using Airflow and Docker Compose.
Full implementation is available on GitHub:
What is Airflow?
Airflow is an open-source platform used for creating, scheduling, and monitoring workflows. It is commonly used in data engineering, data science, and machine learning to create and manage complex data pipelines.
