Glossary

What is Data trust vs. data quality?

Updated September 1, 2026

Data quality asks whether a record is complete, correctly formatted, and free of errors. Data trust asks a harder set of questions: where did this data come from, was consent obtained properly, how current is it, does it corroborate with independent sources, and has it been validated against outcomes. A record can be perfectly clean and completely untrustworthy.

Most organizations measure quality because quality is measurable inside the record itself. Trust requires context the record does not carry on its own: chain of custody, consent scope, corroboration, and clinical linkage.

This is also the difference between infrastructure trust and data trust. Cloud platforms secure the warehouse and call that trust; the data inside is exactly as reliable as it was when it arrived. SuperTruth scores the data itself, before it reaches any warehouse or model.