Prioritizing remediation activities
When you first run your data quality Rule Results Report (or your equivalent), it may be a little overwhelming. There will be failed records for every rule and sometimes the failed records may add up to many thousands. It is not uncommon in larger businesses for 250,000 or more records to fail a rule. For example, if a fast-moving consumer goods organization has a reward card scheme, it can easily have millions of customers. One of the largest of these schemes in the UK has 18 million customers. It would only take a single missing validation on an online enrollment form to generate large quantities of failed data as customers make mistakes when entering data. One organization we worked with required the date of birth of the customer, but did not validate what was entered. Around 1% of customers entered the correct day and month of birth but accidentally entered the current year instead of their birth year. The form was missing a simple validation...