: Data quality (DQ) is emerging as a new relevant area for the improvement of the effectiveness of organizations. Despites the consequences of poor quality of data are often experi...
Carlo Batini, Daniele Barone, Michele Mastrella, A...
We propose a data warehousing architecture for effective risk analysis in a banking scenario. The core of the architecture consists in two data mining tools for improving the qual...
Gianni Costa, Francesco Folino, Antonio Locane, Gi...
Dirty data is a serious problem for businesses leading to incorrect decision making, inefficient daily operations, and ultimately wasting both time and money. Dirty data often ari...
[Context and motivation] When developing software, coordination between different organizational units is essential in order to develop a good quality product, on time and within b...
The dramatic increase in data in the area of cancer research has elevated the importance of effectively managing the quality and consistency of research results from multiple prov...
Andrew F. Hart, Chris Mattmann, John J. Tran, Dani...