首页    期刊浏览 2025年07月07日 星期一
登录注册

文章基本信息

  • 标题:Retail Data warehouse Customer Analytics using ElegantJ BI
  • 本地全文:下载
  • 作者:B.Sarathkumar ; C Kamaraj ; P Saravanakumar
  • 期刊名称:International Journal of Innovative Research in Computer and Communication Engineering
  • 印刷版ISSN:2320-9798
  • 电子版ISSN:2320-9801
  • 出版年度:2016
  • 卷号:4
  • 期号:4
  • 页码:5113
  • DOI:10.15680/IJIRCCE.2016.0404126
  • 出版社:S&S Publications
  • 摘要:In today's competitive environment, analyzing data to predict market trends and to improve organizational performance is an important business activity. As businesses continue to use Information Technology (IT) for a growing number of functions, the firms face the challenge of processing and analyzing huge amounts of data and turning them into profits. In response, the retail industry in particular is trying to revisit and upgrade its business strategies by introducing Business Intelligence (BI) and Data Warehousing (DW). DW is becoming necessary nowadays for the retail sector in India and is widely acceptedfor state-of-the-art decision support. This project is used to deliver a solution in the area of BI and DW for our Retail Giant Client in India. The paperoffers the case handling, DW and BI architecture of our client by focusing on and identifying the business challenges to maintain its vision.Customer analytics is a process by which data from customer behaviour is used to help make key business decisions via market segmentation and predictive analytics. This information is used bybusiness foe direct marketing, site selection, and customer relationship management. Marketing provides services in order to satisfy customers. Withthat in mind, the productive system is considered from its beginning at the production level, to the end of cycle, the consumer. Customer analytics is playing a very important role in prediction customer data and implementing it into somereports
  • 关键词:Retail Management; Data warehouse; Business Intelligence(BI); Customer Analytics; ElegantJ BI; Key Performance Indicator (KPI); Decision Support System (DSS).
国家哲学社会科学文献中心版权所有