Advances in Economics, Management and Political Sciences
- The Open Access Proceedings Series for Conferences
Proceedings of the 2nd International Conference on Financial Technology and Business Analysis
Series Vol. 64 , 28 December 2023
Open
Access | Article
Application of Big Data Analysis in Sales Forecasting
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Abstract
As a matter of fact, with the rapid development of the computation ability and data delivering, the big data analysis becomes a common tool to realize the predictions. With this in mind, this paper focuses on the impact of big data analysis on sales forecasting, starting with an introduction to the present-day context and significance of sales forecasting and some of the forecasting scenarios implemented by previous generations based on machine learning. After introducing these backgrounds, we start to introduce big data analysis and its impact on sales forecasting. According to the analysis and the summaty of the previous experience, we introduce the commonly used models, the parameters of the models, and the evaluation of the models as well as the application scenarios, and the specific application results. Finally, we demonstrate the limitations as well as future perspectives of big data analysis and sales forecasting. Overall, these results shed light on guiding further exploratio of bigdata analysis in sales prediction.
Keywords
big data analysis, sales prediction, sales forecasting model
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Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 2nd International Conference on Financial Technology and Business Analysis
- ISBN (Print)
- 978-1-83558-229-9
- ISBN (Online)
- 978-1-83558-230-5
- Published Date
- 28 December 2023
- Series
- Advances in Economics, Management and Political Sciences
- ISSN (Print)
- 2754-1169
- ISSN (Online)
- 2754-1177
- DOI
- 10.54254/2754-1169/64/20231465
- Copyright
- 28 December 2023
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited