Sales forecasting using data warehouse and Naïve Bayesian classifier

Organizations need to analyze their day to day sales information in order to forecast the sales of their products and services. This forecasting can be used to increase the production of products to meet the demand or can be used to take corrective measures to increase the sales. This paper presents a novel method of sales forecasting using fuzzy logic, data warehouse and Naïve Bayesian classifier. Experiments are performed using sales data of five years collected from many shops located in different cities to prove the efficiency of proposed mechanism.