In the retailing industry, database is the time and place where a retail transaction is completed. E-business processes are increasingly adopting databases that can obtain in-depth customers and sales knowledge with the big data analysis. The specific big data analysis on a database system allows a retailer designing and implementing business process management (BPM) to maximize profits, minimize costs and satisfy customers on a business model. Thus, the research of big data analysis on the BPM in the retailing is a critical issue. The paper aims to discuss this issue.,This paper develops a database, ER model, and uses cluster analysis, C&R tree and the a priori algorithm as approaches to illustrate big data analysis/data mining results for generating business intelligence and process management, which then obtain customer knowledge from the case firm’s database system.,Big data analysis/data mining results such as customer profiles, product/brand display classifications and product/brand sales associations can be used to propose alternatives to the case firm for store layout and bundling sales business process and management development.,This research paper is an example to develop the BPM of database model and big data/data mining based on insights from big data analysis applications for store layout and bundling sales in the retailing industry.

中文翻译：

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有关商店布局和捆绑销售的业务流程和管理的大数据分析

在零售行业中，数据库是完成零售交易的时间和地点。电子商务流程越来越多地采用数据库，该数据库可以通过大数据分析获得深入的客户和销售知识。通过对数据库系统进行特定的大数据分析，零售商可以设计和实施业务流程管理（BPM），以实现利润最大化，成本最小化并在业务模型上满足客户需求。因此，对零售业中BPM的大数据分析研究是一个关键问题。本文旨在探讨这一问题。本文开发了一个数据库，ER模型，并使用聚类分析，C＆R树和先验算法作为方法来说明大数据分析/数据挖掘结果，以生成业务智能和流程管理，