Checks whether the data behind a proposed AI or analytics initiative is actually good enough to build on — completeness, labeling quality, governance, and bias — before funding or engineering time is committed. Use before any AI feature, model, or analytics initiative is approved, and whenever a project is underperforming and the data itself is a suspect.
