A treatise on data quality and a structured approach for improving data quality for an air carrier surveillance program

There are a number of significant challenges in the collection, storage, and analysis of data. Databases that support a diverse set of users and have multiple sources and contributors present significant challenges in sustaining data quality. As data are increasingly used to support activities, the potential increases for negative impacts of poor data quality on organizational effectiveness and efficiency. Efforts to increase and sustain data quality are paramount to good business practices. This paper addresses data quality and proposes a structured approach using statistical applications for improving data quality for an air carrier. The structured approach uses a continuous improvement methodology based on the premise that improvement comes from the application of knowledge. Indicators and impacts of poor data quality are considered, and a hierarchical approach to data quality using data quality attributes, dimensions and categories, as well as a framework for improving data quality are presented.