|Title||Sales prediction and business decision making.|
|Authors/Creators||Aung Pyae (TP052143)|
Sales prediction performs an important role in every market process and the decision-making for sales of products is important to follow the demand of consumers. This research focuses on the study of sales prediction and business decision-making for e-commerce retail businesses with a data science research approach. The main goal of the research is to perform data science analysis on collected sales data with minimum predictor variables to create an advanced sales prediction model to forecast future sales performance and identify new business decisions depending on the predicted results and data analysis report. Applying business intelligence, statistical modeling, and machine learning are proposed to create an intelligent prediction and analytical solutions of retail business, and optimization methods are also applied to create business decisions. Business decisions are made depending on analysis results using mathematical programming methods to set profitable decisions which can minimize or maximize capital and control the stock with decision results. The research mainly depends on the quantitative study in which statistical modeling techniques are applied using different predictive models and results gained are also in quantitative form. The result of this research is solving additional sales problems in an online retail environment using predictable machine learning, statistical data analysis, business intelligence, and applied operational research. The case study, methodology, and decision are made from point of data science and business analyst view.
|Supervisor||Booma Poolan Marikannan, Dr.|
|Institution||Asia Pacific University of Technology and Innovation (APU)|
|School||Graduate School of Technology|
|No. of pages||97|
|Refereed||Yes, this version has been refereed|
A thesis submitted in fulfillment of the requirement of Asia Pacific University of Technology and Innovation for the award of the degree of MSc. in Data Science and Business Analytics (UCMF1808DSBA).
Retail market ; Online businesses ; Decision making ; Regression model ; Neural network ; Forecasting ; Business intelligence ; Marketing ; Competitiveness ; Strategies ; Internal decision ; External decision ; Sales prediction.
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