In business context, sale prediction plays a key role in helping companies making better business decisions. It helps in overall companies in the tasks of planning, budgeting, and financial risk evaluation. Sale forecasting is very important because it allows companies to accurately estimate their costs and revenue, as well as manage companies’ cash flow based on their short-term and long-term financial performance. However, forecasting an accurate is a major challenge for most companies. In this project, based on historical data collected from 1559 products across 10 stores, I use predictive analytics to investigate the relationship between the sale outcome and other factors, namely, when, where and what kind of product sold in store. I build a linear model to use for strategic decisions, supporting companies in decision making (for example, if they need to stock up on goods to meet customer demands, how they price a product to obtain the highest profit, etc.) Link: https://www.kaggle.com/devashish0507/big-mart-sales-prediction
big-mart-sales-prediction's Introduction
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