Data quality rules based on a data profile
Data profiling has proven to be a powerful way for you to learn more about the data you use on your customer report. You are even able to see what a potential data quality score for a field may be just by reviewing the profile.
Which data quality rules can you propose based on the data profile? You can confirm business context for the rules with a data consumer later.
Customer Table Data Profile:
- CustomerPaymentStatus is populated with the following values:
- 70% "Current", 5% "Past Due", and 25% "Paid in Full".
- The average increase in record count in the Customer Table over the last 30 days is 145 records per day.
- CustomerSatisactionScore is populated for 99% of records.
This exercise is part of the course
Introduction to Data Quality
Hands-on interactive exercise
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