Data quality is recognized as an important property of all types of data. Data are of high quality “if they are fit for their intended uses in operations, decision making, and planning” (Juran, 2004). There are a number of theoretical frameworks for understanding data quality: systemstheoretical approach (Ivanov, 1972), product and service perspectives approach (Kahn et al. 2002), semiotics approach (Price and Shanks, 2004), and ontology approach (Wand and Wang, 1996). This study looks at data mining as an approach to identifying data quality issues that are likely to be found in databases to prepare for further analysis in order to answer a question on hand.
