FORECAST OF SALES OF WALMART STORE USING BIG DATA APPLICATIONS

Anita S. Harsoor, Anushree Patil

Abstract: Many household products are sold by various subsidiaries of the retail store network which are geographically located at various locations. Supply chain inefficiencies will occur at different locations when the market potential will not evaluated by the retailers. Many times it is not easy for the retailers to understand the market condition at various geographical locations. The organization of retail store network has to understand the market conditions to intensify its goods to be bought and sold so that many number of customers get attracted in that direction. Business forecast helps retailers to visualize the big picture by forecasting the sales we get a general idea of coming years if any changes are needed then those changes are done in the retail store’s objective so that success is achieved more profitably .It also helps the customers to be happy by providing the products desired by them in desired time, when the customers are happy then they prefer the store that provides all the resources they need to their satisfaction by this the sales in the particular store in which the customers purchase more items increases causing more profit. The forecasting of sales helps to know the retailers the demand of the product. In this paper we make an attempt by understanding the retail store business’s driving factors by analyzing the sales data of Walmart store that is geographically located at various locations and the forecast of sales for coming 39 weeks is done. By sales forecasting the retail networks are supported so that the resources can be managed efficiently.

Keywords: Hadoop, Hive, Big data, Map reduce, Holt winters

DOI: https://doi.org/10.15623/ijret.2015.0406008