Proceedings of the 2021 International Conference on Social Development and Media Communication (SDMC 2021)

Development and Upgrading Plan for FMCG Industry Based on Data Mining

Authors
Feiyang Liurainaliufeiyang@hotmail.com
Accounting, Eli Broad of Business, MSU, Michigan, United States, 48824
Corresponding Author
Available Online 17 January 2022.
DOI
10.2991/assehr.k.220105.140How to use a DOI?
Keywords
Data Mining; FMCG Industry; Development and Upgrading Plan
Abstract

With the increasing amount of data in the enterprise, more and more managers need to understand the integrated data and historical data in the operations. Thus, many companies have the problem of how to use the data resources of each part rationally and assist the senior management of the company to complete relevant decision analysis. In this paper, the management platform system of FMCG industry will be taken as an example to discuss how to establish a data warehouse based on traditional database management, how to implement the classification of data mining objects, the preparation of data mining model and big data analysis, and the application of new data mining model.

Copyright
© 2022 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article under the CC BY-NC license.

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Volume Title
Proceedings of the 2021 International Conference on Social Development and Media Communication (SDMC 2021)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
17 January 2022
ISBN
10.2991/assehr.k.220105.140
ISSN
2352-5398
DOI
10.2991/assehr.k.220105.140How to use a DOI?
Copyright
© 2022 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Feiyang Liu
PY  - 2022
DA  - 2022/01/17
TI  - Development and Upgrading Plan for FMCG Industry Based on Data Mining
BT  - Proceedings of the 2021 International Conference on Social Development and Media Communication (SDMC 2021)
PB  - Atlantis Press
SP  - 766
EP  - 771
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.220105.140
DO  - 10.2991/assehr.k.220105.140
ID  - Liu2022
ER  -