So , we must find new ways to extract potentially useful information and knowledge from data . data mining and kdd aim to provide neoteric techniques and tools to automatically analyze the data , to automatically classify it , to automatically summarize it , to automatically discover and characterize trends in it , and to automatically flag anomalies 数据挖掘技术和kdd (数据库中的知识发现)系统作为一种崭新的技术和工具，能自动地分析数据、自动地对数据分类、自动地对数据汇总、自动地发现和描述数据中的趋势、自动地标记异常。
So data mining technology that apply machine learning to large database to acquire useful information from a lot of data is developed . data mining ( dm ) or knowledge discover database ( kdd ) is to discover useful information and potential knowledge from plentiful and uncompleted and noise and fuzzy and random data which are hided and not known by people 所谓数据挖掘( datamining ， dm ) ，也可以称为数据库中的知识发现( knowledgediscoverdatabase ， kdd ) ，就是从大量的、不完全的、有噪声的、模糊的、随机的数据中，提取隐含在其中的、人们事先不知道的、但又是潜在有用的信息和知识的过程。
Data mining is called knowledge discovery in database in the data base founding . it is defined to pick up shield , unknown and uncommon , latent message and model in the large or data warehouse . it is a new field with high value melt many theory and technology such as database , ai , computer studying , accounting etc . association analyst , relational analyst , forecast analyst , clustering analyst are all key method of data mining 数据挖掘( datamining ) ，又称数据库中的知识发现( knowledgediscoveryindatabase , kdd ) ，是指从大型数据库或数据仓库中提取隐含的、未知的、非平凡的及有潜在应用价值的信息或模式，它是数据库研究中的一个很有应用价值的新领域，融合了数据库、人工智能、机器学习、统计学等多个领域的理论和技术。
