Data mining challenges and knowledge discovery in real life applications

Data mining techniques have increasingly been studied specifically in their application in real-world databases. One typical problem is that databases tend to be very large, and these techniques often repeatedly scan the entire set. Sampling has been used for a long time, but subtle differences among sets of objects become less evident. This paper aims to bring attention to some of the fundamental challenging questions faced in applying data mining with the hope that future research aims to resolve these issues. This paper is organized as follows: Section 2 briefly discusses the KDDM process models and basic steps proposed for applying data mining. Section 3 discusses the fundamental questions faced during data mining application process. Section 4 concludes the paper.