Data quality practices measure and improve accuracy, completeness, consistency, and timeliness of datasets used by AI systems.
AI Glossary
Data Quality
Coverage in development
Data quality practices measure and improve accuracy, completeness, consistency, and timeliness of datasets used by AI systems.
Definition
Plain English explanation
Making sure the inputs are correct, complete, and fresh enough to trust.
Related glossary terms
Last reviewed
Sources
- NIST AI Risk Management Framework — risk vocabulary context for AI systems
- Brel Digital company and technology profiles — applied usage evidence where tagged
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