Data Quality Scorecard (Monitoring)


Score decompositions can be built along many dimensions :

  • data elements
  • data quality rules
  • subject populations
  • record subsets.

Score Decompositions (report, answers)

Decomposition may indicate that :

  • in 80% of cases it is caused by the problem with the employee compensation data; in 15% of cases the reason is missing or incorrect employment history; and in 5% of cases the culprit is invalid date of birth.
  • over 70% of errors are for employees from a specific subsidiary. This may suggest a need to improve data collection procedures in that subsidiary.
  • 6.3% of all calculations are incorrect because of data quality problems, such a score is extremely valuable


Data quality scorecard is a valuable analytical tool that allows to :

  • measure the cost of bad data for the business
  • estimate ROI of data quality improvement initiatives
  • allow us to make better decisions and take actions


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