Data Quality Scorecard (Monitoring)

Dimension

Score decompositions can be built along many dimensions :

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

Articles Related

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

Summary

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

Reference

• Monitoring Data Quality Performance Using Data Quality Metrics with David Loshin