摘要
针对电商企业数据的复杂性与管理需求,文章设计了基于Power BI的数据仓库可视化平台。首先通过高效采集和深度分析电商数据,揭示销售趋势与用户行为特征。随后,融合数据深度挖掘技术与直观可视化技术,以完成平台的整体设计。实验结果表明,随着线程数的增加,该平台数据处理时间从1200 s大幅缩短至380 s,存储速率则从10 MB/s提升至31 MB/s,同时库存变动监控的实时性也得到显著提升,整体应用效果较好。
In response to the complexity and management needs of e-commerce enterprise data,this article designs a data warehouse visualization platform based on Power BI.Firstly,by efficiently collecting and deeply analyzing e-commerce data to reveal sales trends and user behavior characteristics.Subsequently,data deep mining technology and intuitive visualization technology were integrated to complete the overall design of the platform.The experimental results show that as the number of threads increases,the data processing time of the platform is significantly reduced from 1200 s to 380 s,and the storage rate is increased from 10 MB/s to 31 MB/s.At the same time,the real-time monitoring of inventory changes is also significantly improved,and the overall application effect is good.
作者
李骜成
潘建江
BI LI Aocheng;PAN Jianjiang(School of Economics and Business Administration,Chongqing University,Chongqing 400030,China)
出处
《无线互联科技》
2025年第3期98-101,共4页
Wireless Internet Science and Technology
作者简介
李骜成(2001-),男,学士,研究方向:信息管理,大数据管理。
