What data-quality checks do you put on a pipeline, and how do you catch bad data before it spreads?

Bad data quietly corrupts everything downstream (dashboards, models, decisions), and 'it ran without error' is not the same as 'it's correct.' The signal is the categories of checks and failing loud at the boundary.

Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.