Data Mining Techniques and Trends – A Review

Everyday Terabytes of data are generated in many organizations. So it’s difficult to predict for the world. Because of data are increasing day by day, we requires a need for new tools and techniques to support humans in automatically and intelligently analyzing large datarepositories toobtain useful information. These growing needs gives a vison for a new area of research field called Data Mining (DM) or Knowledge Discovery in Databases (KDD).DM aims to extract implicit, previously unknown and potentially useful information from data by digging intelligently in large data repositories. In another waywe can say thatDM techniques are needed/used to extract unknown predictive information from large mass of data.Now a days data mining enhanced the various fields of human life including business, education, agriculture, medical, scientific etc., using Artificial Intelligence, Statistics, Computation capabilities, Pattern Recognition and Machine Learning, data visualization techniques. So we can say that DM has become an essential component in various fields of human life.This paper discusses and describes DM and major DM techniques such as statistics, artificial intelligence, decision tree approach, genetic algorithm, and visualization.