Data mining is an emerging research field in database and artificial intelligence. In this paper

the data mining techniques are introduced broadly including its producing background

its application and its classification. The principal techniques used in the data mining are surveyed also

which include rule induction

decision tree

artificial neural network

genetic algorithm

fuzzy technique

rough set and visualization technique. Association rule mining

classification rule mining

outlier mining and clustering method are discussed in detail. The research achievements in association rule

the shortcomings of association rule measure standards and its improvement

the evaluation methods of classification rules are presented. Existing outlier mining approaches are introduced which include outlier mining approach based on statistics

distance|based outler mining approach

data detection method for deviation

rule|based outlier mining approach and multi|strategy method. Finally

the applications of data mining to science research

financial investment

market

insurance

manufacturing industry and communication network management are introduced. The application prospects of data mining are described.