Abstract
The domain of data mining is discussed with respect to various information technologies such as pattern recognition, neural networks, machine learning and knowledge based systems. Pattern revelation with information granules and information granulation is described as the method to cope with abundance of detailed numeric data. Granulation and information granules are carried out in the frameworks of set-based environments and probability. The advantages of information granules are discussed in correlation to end-users, classes of membership functions and incorporation of data mining, associations and rules.