Data quality requirements analysis and modeling

A set or premises, terms, and definitions for data quality management are established, and a step-by-step methodology for defining and documenting data quality parameters important to users is developed, demonstrating that data quality can be an integral part of the database design process.

Abstract

A set or premises, terms, and definitions for data quality management are established, and a step-by-step methodology for defining and documenting data quality parameters important to users is developed. These quality parameters are used to determine quality indicators about the data manufacturing process, such as data source creation time, and collection method, that are tagged to data items. Given such tags, and the ability to query over them, users can filter out data having undesirable characteristics. The methodology provides a concrete approach to data quality requirements collection and documentation. It demonstrates that data quality can be an integral part of the database design process. A perspective on the migration towards quality management of data in a database environment is given.>