In the ever-evolving landscape of retail, the utilization of data-driven insights plays a pivotal role in enhancing decision-making processes. This research paper delves into the development and implementation of an interactive visualization system tailored specifically for the analysis of data within a supermarket store environment. In order to predict the sales of a business, an intelligent model was built using Linear-Regression, LASSO-regression and XG-Boost techniques which has been shown to be more effective than existing models.