Rough sets as a tool in data engineering

The main objective of this paper is to introduce the Pawlak's rough sets theory as a tool in data engineering and, more precisely, in dependencies discovering from data. In this field, two different kinds of tabular representation of knowledge are used: KRS tables and decision tables. Using decision tables the authors show how useful consequences may be inferred from real data collected in their academic community.