A measure of how well data meets the needs of its intended use, covering accuracy, completeness, consistency, timeliness, validity, and uniqueness.
The six dimensions of data quality are: accuracy (does it correctly represent reality?), completeness (are all required values present?), consistency (is it formatted the same way throughout?), timeliness (is it current enough?), validity (does it conform to defined rules?), and uniqueness (are there no duplicates?).
Poor data quality leads to wrong decisions, wasted resources, and loss of trust. Improving data quality requires both fixing existing problems and preventing new ones.