数据统计分析中应用数据挖掘技术及效益分析

Application of Data Mining Technology and Benefit Analysis in Statistical Analysis

传统的数据统计分析方法是利用数据库系统已有的数据进行简单的统计归类分析,可以方便快捷对数据进行录入、查询、修改、更新、统计等功能。但是传统数据统计分析方法无法及时准确地发现数据中存在的关系和规则,无法快速提取企业决策者需要的精准分析数据,致使企业决策者很难根据现有的统计数据预测未来的发展趋势。很容易丢失商机,造成企业的被动,为企业发展壮大带来巨大的阻力。因此急需一种新的技术来实现企业的这些需求。本文重点分析的数据挖掘技术可以替代对海量数据无法胜任的传统数据统计分析方法,它将传统的数据分析方法与处理大量数据的复杂算法相结合。数据挖掘为探查和分析新的数据类型以及用新方法分析旧有数据类型提供了强大准确的处理能力,在海量数据处理方面得到广泛应用并取得非常好的经济及社会效益。

The traditional statistical analysis method is to use the existing data of database system to carry out the simple statistical classification analysis. It can easily and quickly input, query, modify, update and count the data. But the traditional statistical analysis methods can not timely and accuratly discover the relationships and rules of data, and it can not quickly extract accurate the precision analysis data needed by the business decision-makers, which makes the business decision makers is difficult to predict future trends based on existing statistical data. So, it is easy to lose business opportunities, makes the enterprise is passive and enormous resistance to business development and growth. Therefore, it is urgent to need a new technology to achieve these requirements. This article focuses on the analysis of data mining technology, which can replace the traditional data analysis technology and analyze massive data. It combines the traditional data analysis method with the complex algorithm of processing a large number of data. Data mining provides a powerful and accurate processing power for exploring and analyzing the new data types and analyzing the old data types by using new methods. It has been widely used in massive data processing and has achieved very good economic and social benefits.