DATA MINING AND KDD - PROMISE AND CHALLENGES

Databases are growing in size to a stage where traditional techniques for analysis and visualization of the data are breaking down. Data min ing and knowledge discovery in databases (KDD) are concerned with extr acting models and patterns of interest from large databases. Data mini ng techniques have their origins in methods from statistics, pattern r ecognition, databases, artificial intelligence, high performance and p arallel computing, and visualization. In this article, we provide an o verview of this growing multi-disciplinary research area, outline the basic techniques, and provide brief coverage of how they are used in s ome applications. We discuss the role of high performance and parallel computing in data mining problems, and we provide a brief overview of a few applications in science data analysis. We conclude by listing c hallenges and opportunites for future research.