Big data analysis on the business process and management for the store layout and bundling sales

Purpose: 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. Design/methodology/approach: 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. Findings: 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. Originality/value: 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.