Data Mining Technology in Business Data Analysis

Abstract

Abstract With the vigorous development of e-commerce, people pay more and more attention to data mining technology. This research mainly discusses the application of data mining technology in business data analysis. This study uses the clustering algorithm of buyers’ purchasing behavior as an example to illustrate the definition of VMML in the clustering analysis of purchasing behavior. In this piece of XML, through the integration of data, an e-commerce research data warehouse is constructed, which is also used as the source data of EBizDAS. A certain amount of research has been done on buyers, sellers, commodities and transaction data, and the results obtained by EBizDAS analysis are displayed on the C2C e-commerce data analysis web platform for C2C users to browse and reference online. In this study, the 10 queries in CoHadoop took a total of 849 seconds, while the distributed strategy took a total of 748 seconds, with a performance improvement of about 12%, and the overall performance improvement was still considerable. This research has positive significance for the development of e-commerce.