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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

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