数据挖掘技术及其在经营分析系统中的应用

为了在市场竞争中保持及发展客户、提升客户价值,运营商迫切需要了解客户的行为特征以及业务发展、收益、营销、服务等方面的运营情况,以便及时制定更加合理和高效的经营策略,更好地在竞争中掌握主动.于是,电信企业纷纷着手建立数据仓库和在线分析处理(OLAP)系统,通过对运营支撑系统多年积累的业务数据进行整合和分析,以获得有价值的分析结果.但是,OLAP侧重的是对历史数据的分析,回答的是"过去发生了什么和为什么会发生"的问题,而运营商在对过去和现在的经营状况进行分析掌握的同时,更加渴望对整个企业未来的发展状况做出比较完整、合理、准确的分析和预测,于是,数据挖掘技术由于能够发现潜在的知识以及能够回答"将要发生什么"的问题而被电信企业加以"重用".本文简要阐述了数据挖掘技术、主要模型及方法、数据挖掘的实施步骤,并结合具体的案例说明数据挖掘在电信行业经营分析系统中的应用.

Data Mining and Its Application in Telecom Business Analysis Support System

Along with the competitive market it is getting more and more urgent for telecom operators to obtain the knowledge about their customers, marketing, service and other business status. More and more data warehouses and OLAP systems are set up to help telecom operators to make business decisions efficiently and effectively. Compared with OLAP applications, which specialize in verification-driven analysis, data mining are playing a more important role in telecom business intelligence applications. Operators are paying more attentions and forces into data mining applications, which can help them to get the hidden knowledge under the mass operational data, to make a proper forecast for their business development. In this article there are some brief introductions of data mining technology, the main data mining models and methods, the normal steps of a data mining fulfillment. Also it gives an illustration of data mining application in telecom business analysis support system.