Association and Classification Analysis in Retail Case Study

Data mining has become increasingly commonplace and is used in a variety of domains. Data mining have various applications which affect in several fields of human. Such fields use data mining widely to enhance researches, increase sales, decrease costs and understand customer’s behavior. This study proposes a new framework based on data mining algorithms for the giant fashion Retail Companies. Our aim is to make it easy for an organization uses business intelligence capabilities, including reporting, visualizations, integration and data mining by discussing the difference between widely used algorithms in data mining and how it can be used in the retail field especially classification and association analysis. Data Mining is really a multidisciplinary area focusing on methodologies for extracting valuable knowledge from database understanding of customer’s behavior. The main goal of the paper is to illustrate the importance of optimization methods used in the data mining process, as well as the specific predictive models and how they work in this field. The study reinforces and demonstrates the validity and efficiency data mining techniques can play and their important role in both small and large data sample datasets which provide additional empirical evidence regarding to merits of data mining techniques in retail.