Data quality
Rules data must satisfy, and the measured results of checking it against them.
Also called: DQ
Data quality is the gap between what data should be and what it is. Rules ("never negative", "not null", "matches the reference list") are checked, scored and monitored. Active data quality blocks or flags bad data before it reaches a critical report.
Example: "Outstanding balance must be ≥ 0 and not null": 99.7% pass this run.
Not to be confused with data profiling, which only describes.