Intelligent Prediction and Analysis of Online and Offline Retail Big Data Under the Background of Public Health Emergencies
- DOI
- 10.2991/978-94-6463-064-0_121How to use a DOI?
- Keywords
- big data; online shopping; tableau; intelligent algorithms; predictive evaluation
- Abstract
With the rapid iterative upgrade of digital economy and internet plus, online shopping experience has been more and more widely accepted and loved by the public. Especially in the case of public health events such as COVID-19 outbreak, e-commerce transaction has become the mainstream format. This paper collects the big data of supermarket sales, makes visual analysis of the data through intelligent algorithms such as machine learning with Tableau as the main body, and carries out the transaction situation, profit, sales and sales forecast and evaluation of various provinces and cities. It is considered that online shopping is continuously impacting offline shopping, and experiential scenes are accelerating the replacement of traditional physical stores.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yue Liu AU - Zongguo Zhang PY - 2022 DA - 2022/12/27 TI - Intelligent Prediction and Analysis of Online and Offline Retail Big Data Under the Background of Public Health Emergencies BT - Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022) PB - Atlantis Press SP - 1159 EP - 1167 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-064-0_121 DO - 10.2991/978-94-6463-064-0_121 ID - Liu2022 ER -