  Rough set theory is a new method that deals with vagueness and uncertainty
emphasized in decision making. Data mining is a discipline that has an
important contribution to data analysis, discovery of new meaningful knowledge,
and autonomous decision making. The rough set theory offers a viable approach
for decision rule extraction from data.This paper, introduces the fundamental
concepts of rough set theory and other aspects of data mining, a discussion of
data representation with rough set theory including pairs of attribute-value
blocks, information tables reducts, indiscernibility relation and decision
tables. Additionally, the rough set approach to lower and upper approximations
and certain possible rule sets concepts are introduced. Finally, some
description about applications of the data mining system with rough set theory
is included.
