Integrity analysis: methods for automating data quality assurance

Abstract Data continue to remain a neglected component of electronic data processing (EDP) systems and are largely unsupported by research. As a result, most files contain defective data, and the extent of this condition is not measurable due to a lack of rigorous inspection techniques. Integrity analysis is a formal methodology for inspecting stored data in a systematic manner, and for quantifying data integrity. Problems in both data and systems are detected by automated data constraints. Result reliability of the inspection processes is ensured by algorithms that provide control and auditability whenever data already identified as defective must proceed through subsequent constraints. Integrity analysis principles are applicable to quality assurance, EDP audit, systems design, operations, and management, as well as to the design of data dictionaries, database management systems, and generalized software for data inspection.