Data Quality

Data quality refers to how well data fulfills its intended use based on dimensions like accuracy (does it reflect reality?), completeness (are required fields populated?), consistency (is the same concept represented the same way across records?), and timeliness (is it current enough?).

Low data quality in a price comparison app might mean showing outdated prices that differ from what the retailer actually charges. In a property listing app, it might mean displaying square footage in inconsistent units or showing listings that have already sold.

API providers that invest in data quality implement validation at ingestion, deduplication, anomaly detection, and normalization pipelines. When evaluating an API for production use, look for documentation on quality practices, freshness guarantees, and how errors are surfaced.