Data is ubiquitous and we are now able to collect large quantities of it in complex and distributed software systems such as the cloud. Lot of decision making is also based on analyzing and mining this data. For instance, at the Cancer Registry of Norway a data is collected about patients taking differnet types of screening tests. This data is then exported to reseachers for analysis and they come up with trends in public health and influence policies for new treatments. However, we often fail to ask if the quality of the data is good enough that is complete, correct, valid, and timely to come up with accurate scientific claims that ultimately affect policy. Therefore, there is a need to be able to look at the data quality issues separately. This talk will focus on how we model "high or low" quality data based on the notion of "data interactions" and verify large relational databases for the satisifaction of such models. I will illustrate the functioning of our tool Depict (Discovering Patterns and Interactions in Databases) with data from the Norwegian Customs and Excise department and the Cancer Registry of Norway.