DATA MINING

DATA MINING

ABSTRACT

     This paper deals with concept of  DATA MINING. Data mining is  the semi-automatic extraction  of significant  patterns , changes , associations  and other statistically  significant  structures from large data sets that search for relationships and global patterns that exist in large databases. A data mining tool should unearth hidden predictive information from large database automatically. By this definition data mining is data-driven, not  user-driven or  verification-driven. There is more and more digital data being collected, processed, managed and archived every day. Algorithms, software tools, and systems to mine it  are critical  to  a wide  variety of  problems  in  business , science , national defense, engineering, and health care.
             From a business perspective, data mining's roots are in direct marketing and  financial services. From a technical perspective, data mining is beginning to emerge as a separate  discipline  with  roots in a) statistics    b) machine learning     c) databases  and  d) high performance computing.
           Applications of data mining includes  fraud detection, credit card scoring  and  acquisition , risk management , web mining , enhance customer relations, direct marketing, trend analysis, financial market forecasting , international criminal investigations and personal profile marketing. Exotic Artificial Intelligence-based systems are also being touted as new data mining tools. In this way , the paper highlights the concept of data mining, which search  for ever-increasing mountains of information.