The data excellence framework defines business rules as “a set of rules with which the data should comply in order to execute business processes properly” For each data object (e.g. customer, supplier, bank, material, asset, location, etc.) and for each data quality dimension, a specific set of business rules should be identified, documented and managed. The data object must always be contextualized and linked to the business process during the definition of any business rule related to it. It is important to adopt a practical approach to data quality and to focus on a smaller set of critical business rules rather than seeking 100 percent data quality, which may never be achieved or required. An optimal level of data quality needs to be targeted in order to maximize the business value and avoid delays. The set of business rules supporting data quality grows over time as part of the process of continuous improvement.
Examples of some common business rules are as follows :
- A customer order record must have a non-obsolete product code (SKU)
- A customer record must have a current credit score for an order to be processed
- A customer record must have a valid date of birth for the record to be included in marketing campaigns where age is a requirement
- Email address must be populated to be included in internet marketing campaigns
- Contract start date must be before date of birth to validate consistency of the contract start date
- All bank records must have the ISO country code in the 5th and 6th digits of the SWIFT code to validate the SWIFT code
- Currency code must be consistent with country code to validate consistency of the currency code and the country code