Evaluation of Impact of Data Quality on Clustering with Syntactic Cluster Validity Methods

In this research the influence of four most commonly used data quality dimensions (accuracy, completeness, consistency and timeliness) on clustering outcomes was studied. Statistical significant negative effect of low data quality levels on results of different clustering algorithms was demonstrated. The relationship between Data Quality concepts and clustering concepts were constructed and some recommendations on usage of clustering algorithms with respect to data quality level were made.