Data Quality Score Meter

The data quality score is an aggregated value between 0-100 that represents a summary of the integrity of your data. A score of 100 means that Collibra DQ does not detect data quality issues in your dataset. Conversely, a score of 0 indicates that Collibra DQ has observed enough potential data quality issues that it has down-scored the findings to the lowest possible value.

Note The findings from each data quality dimension where Collibra DQ detects potential data quality issues contribute to the overall data quality score.

Below the score meter are five clickable options plus a time stamp.

Data Quality Score meter

No.	Component	Description
	Pass	Runs that failed but after investigation were valid. Train the model to pass future runs that are similar.
	Fail	Runs that passed but after investigation were invalid. Train the model to fail future runs that are similar.
	Off-Peak	A valid run that does not align with peak time runs, for example, over a weekend or a holiday. Label as Off Peak to train the model to recognize the pattern for future runs.
	Ignore	A valid run that fits the run cycle profile but should not be used for training. You simply want to ignore.
	Delete	Runs that triggered by mistake and should be removed.
	Timestamp	The runId of the current DQ Job. When there is only one DQ Job run on a given runId date, the timestamp is always 00:00. However, when there are multiple DQ Job runs on a given runId date, the timestamp reflects the time each DQ Job ran, for example, 01:00 or 10:45.