Research And Application Of Data Mining For Narada Power Company Information System

Recently, with the rapidly development of the power source industry, the scale of power enterprise become more magnificence and market competition also become more serious among enterprises. It has to consider a situation how to improve the competitiveness of enterprises in all sectors. More and more companies recognize that their customers are important strategic resources and the lifeblood of business, how to retain existing customers and develop new customers, has become an important work the companies need to consider. While data mining, as an advanced data analysis methodology, is an effective tool for the in-depth analysis of customer data.This paper started with summarizing the features and status of the informationization of power source industries, analyzed the features and the existing problems. This paper took a power source enterprise in Zhejiang province as object, analyzed the demands of the customer relationship management system, and presented a data mining solution suitable. The main contents are summarized as follows.(1)Researched main algorithms of data mining, analysed business characteristics of power source company and customer relationship management detailedly. After in contrast and analysis of the main method of data mining, supply applicable data mining algorithm for the enterprise in view of data characteristic, using clustering analysis to segment customers, using time series to forecast sales.(2)Presented a scheme of data warehouse, which is suitable for this company’s acquisition, then introduced the procedure of data preprocessing and the design and realization of data mining mode from the point of application. Has built mining mode for customer segmentation based on cluster analysis and mining mode for sales forecasting based on time seriesThis thesis applies data mining technology in battery manufacturer, providing decision support for company, offering the technic guarantee of the marketing strategy, improving quality of service. It has great significance to enhance the competitiveness of enterprise, also has reference value for the application of data mining in production enterprise.