Turn catalog uncertainty into visible, assignable work.
Use profiling, validation, review queues, source reliability and guarded commit controls so bad data does not silently become canonical truth.
Detect different failure modes at the stage where they are understandable.
A schema problem, a normalization problem and a dangerous catalog change need different evidence and different resolution paths.
Structural drift
Removed fields, incompatible types or missing mapped paths.
Semantic failures
Unknown values, failed transformations or missing required canonical data.
Match ambiguity
Duplicate candidates or insufficient identity evidence.
Blast radius
Unexpected removals, identity regressions or compatibility changes.
Human decisions
Assignments, comments and explicit resolution instead of hidden spreadsheet edits.
Controlled change
Regression/release controls can protect changes to established supplier pipelines.
A clean export is not enough if nobody can explain tomorrow's change.
Lineage, review history, mapping versions and reliability evidence make catalog quality something the team can operate repeatedly.