Data
Managing Data Quality Rules: Exceptions and the Cost of Errors
Architecting Data Quality Rules as a product involves defining clear ownership, establishing an efficient workflow for exceptions, and implementing a methodology for measuring economic impact. This approach ensures data integrity and optimizes costs.
