Data warehouses require and provide extensive support for data cleaning. They load and continuously refresh huge amounts of data from a variety of sources so the probability that some of the sources contain “dirty data” is high. In this paper we present our regular sparsity map editor which can be used for the purpose of detection of specific data errors in the data warehouse systems. We also discuss how it can be used for a selection of relevant dimension elements.
Naydenova, Ina; Kaloyanova, Kalinka; Georgiev, Georgi; and Melkonyan, Pegruhi, "Data Errors And Relevant Dimension Values Detection With A Regular Sparsity Map" (2009). MCIS 2009 Proceedings. 45.