Implementing data quality using rule bases and knowledge engineering

摘要

Knowledge engineering methodology and tools are applied to the problems of data quality and the process of data auditing. Business rules and data conventions are represented as constraints on data which must be met. The data quality system and process of the present invention functions to allow good data to pass through a system of constraints unchecked. Bad data, on the other hand, violate constraints and are flagged. After correction, this data is then fed back through the system. Advantageously, constraints are added incrementally as a better understanding of the business rules is gained.