Supermarket Sales Analysis

Ishita Trivedi
2020 International Journal for Research in Applied Science and Engineering Technology  
The most influencing part of research with supermarket analysis has been data mining which is also gaining popularity for the same. Mining has found to be playing a key role in discovering new trends in data, which is helpful for all areas associated with this field. The process of data mining includes extracting data by automatic and semi-automatic means. Artificial intelligence, machine learning and database management in Data Mining is used for extracting new patterns in huge datasets and
more » ... uge datasets and also gives us the knowledge associated with these patterns. Therefore, data mining can be used in supermarket applications, through which finding out when, why and which product purchase has been the highest and this helps us to increase the sales. This also facilitates the better management of the store since the availability of products also increases. Our project focuses on developing software that will be useful for the supermarket owner as well as its customers. In this paper Seasonal Autoregressive Integrated Moving Average -SARIMA or Seasonal ARIMA, is the extended form of ARIMA (Autoregressive Integrated Moving Average) algorithms are used. It will help the supermarket owner as it will keep updating and notifying about the products with highest sale & products that are going out of stock and products with less sale. It is helpful on the customer's side as it will recommend products to the customers as well as will update them about any prescribed product that is going out of stock.
doi:10.22214/ijraset.2020.30970 fatcat:7djbdkqckndu5afjlj6zqouyzm