A Methodology to Explore Rules and Methods for Data Quality Dimensions Toward Improvement the Quality of Databases

Abstract

Awareness of data quality dimensions and their relationships, poses new challenges to the database provider during the past two decades. Although, information systems have continuous improvement against their data problems, their success progressively depends on their methodology. This paper presents a methodology to measure, analyze and evaluate data quality dimensions by using subjective and objective measurement. Applying empirical methods and data mining techniques are steps of this methodology to improve database quality in the information systems. The applied rules and methods can be used to visualize and analyze attribute identification of the databases which is powerful and efficient to extract and reduce inconsistencies of the data. This methodology can be applied to compute other measurable quality dimensions and can help the information system providers to have intelligent and highly sophisticated opinions on creating databases.