Data Errors And Relevant Dimension Values Detection With A Regular Sparsity Map

Authors

Ina Naydenova, Institute for Parallel Processing, Bulgarian Academy of ScienceFollow
Kalinka Kaloyanova, University of Sofia, Faculty of Mathematics and InformaticsFollow
Georgi Georgiev, University of Sofia, Faculty of Mathematics and InformaticsFollow
Pegruhi Melkonyan, University of Sofia, Faculty of Mathematics and InformaticsFollow

Abstract

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.

Recommended Citation

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.
https://aisel.aisnet.org/mcis2009/45