Automating Impact Analysis: Python Data Lineage for dbt-style Projects

"If I drop this column, what breaks downstream?" It is a simple question that most data teams cannot answer accurately. In this video, we build a complete, column-level data lineage engine from scratch in about 1,000 lines of Python. We bypass the limitations of regex by parsing real SQL syntax trees to trace data dependencies across a realistic 25-model warehouse. You will learn how to track a column's exact blast radius, find the root cause of final mart metrics, and set up a CI gate to block breaking changes before they merge. 🚀 Check Out My Data/AI Courses: https://whop.com/the-data-guy-llc/ Use Code dataguysub for 25% off! 🚀 Get Source Code and Bonus Content: https://patreon.com/TheDataGuy?utm_me... ⚡ Follow my Substack: https://substack.com/@thedataguygeorge