"But it works on my machine." If you spend enough time in data engineering or software development, you will inevitably hear this phrase. You might write a brilliant ETL script that works flawlessly on your laptop, but the moment you move that code to a cloud server, everything breaks. The server has the wrong version of Python, missing libraries or conflicting dependencies. This exact problem is why Docker exists. To understand how Docker works in the real world, we are going to break down its role in a live DataOps project: an automated NBA Analytics pipeline that extracts game statistics and transforms them using Apache Airflow and dbt. What is Docker? Docker is an open source platform for developing, shipping and running applications. Docker enables you to separate your applications from your infrastructure so you can deliver software quickly.…