Improving engineering asset lifecycle data quality: Setting the rules

Business rules are constraints that validate data relationships. They form the cornerstone of the data quality. Understanding the business rules helps with identification and precise classification of the majority of data problems. Enforcing data quality checks and rules in information systems, ensures quality and consistency of data by validating quality of data against business rules at each stage of data lifecycle; thereby not allowing poor quality data to enter the system. Conformance to data quality rules provides a number of benefits to businesses, including enhanced data quality and agility in responding to the ever changing demands of the business environment. It is particularly important for engineering asset management data, since these organisations mature technologically along the continuum of standalone information technologies to integrated systems, and in so doing aim to achieve maturity of processes enabled by these technologies and the information produced by the business processes. This paper outlines the process of data quality business rule design and discusses data quality rules for asset lifecycle data.