Usage of data in various areas and its electronic availability has upgraded the importance of data quality to the highest level. In general, data quality has at least a syntactic and a semantic component. The syntactic component is relatively easily reached, mostly supported by tools, while the semantic component requires further research. In many cases, data is taken from different sources which are distributed among enterprises and vary in levels of quality. Special attention needs to be paid to data upon which critical decisions are met. In the paper we will focus on data quality in connection with conceptual modeling, including reuse of models and/or parts of them and data policy for increasing the quality of data.