Sales Forecasting Using Prediction Analytics Algorithm
- August 29, 2020
- Posted by: RSIS Team
- Categories: Engineering, IJRIAS
International Journal of Research and Innovation in Applied Science (IJRIAS) | Volume V, Issue IV, July 2020 | ISSN 2454-6194
Sales Forecasting Using Prediction Analytics Algorithm
A. Gokilavani1, T. P. Banupriya2, S. Bhagavathi3, A. Divya Bharathi4, T. Tamilselvan5
1Associate Professor, Jai Shriram Engineering College, Tamil Nadu, India
2,3,4,5Student, Jai Shriram Engineering College, Tamil Nadu, India
Abstract: “Sales forecasting using prediction analytics algorithm” is planned for providing a complete analysis of sales forecasting. Sales forecasting is an important aspect of different companies engaged in retailing, logistics, manufacturing, marketing and wholesaling. It allows companies to efficiently allocate resources, to estimate achievable sales revenue and to plan a better strategy for future growth of the company. In this project, prediction of sales of a product from an outlet is performed via a two-level approach that produces better predictive performance compared to any of the popular single model predictive learning algorithms. The approach is performed on Departmental store. The proposed approach was organized into six stages, first is data collection, which includes collecting data and dataset, second is hypothesis definition, which used to analyse the problems, third is data exploration which used to explore the uniqueness of the data, fourth is data cleaning, which is used to detect and correct the inaccurate dataset, fifth is data modelling, which is used to predict the data using machine learning techniques, sixth is feature engineering, which is used to import the data from machine learning algorithm.
