Part 4: This is the fourth of eight posts on how to measure data quality. This post describes why consistency is a good measure and how it’s used.
Consistency refers to information that is required to be in the same format for all records in a database. This is best seem by two example.
Example 1, if we have a salutation field that is used for direct marketing or email marketing purposes, then Dear Steven Gerrad (yes, I’m a Liverpool fan!) or Dear Steven or Dear Mr Gerrad is acceptable, but Dear Gerrad may not be acceptable. The consistency of the salutations is important as it affects your reputation.
Example 2, a call centre that uses phone numbers to automatically dial out from a database may require numbers to be in a particular format, say +442087991313. If a bracket is found the software may not be able to handle the number, causing inefficiency in calling. In this case, consistency of number formats is important for the auto-dialling software to work and the efficiency of the call centre. According to the Seven Dimensions, the number is Complete and Accurate.
Certain field will require consistency if there is a business need for that consistency, otherwise you may want to measure consistent for readability reasons or simply that you have a data standard that must be adhered to.
The other dimensions are:
- Completeness (Part 2 of 8)
- Accuracy (Part 3 of 8)
- Conformity (Part 5 of 8)
- Currency (Part 6 of 8)
- Duplication (Part 7 of 8)
- Integrity (Part 8 of 8)