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Application of Big Data, Blockchain, and Internet of Things for Education Informatization. Second EAI International Conference, BigIoT-EDU 2022, Virtual Event, July 29–31, 2022, Proceedings, Part I

Research Article

Data Mining Analysis Based on Business Administration Data

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-23950-2_42,
        author={Pengfei Ma},
        title={Data Mining Analysis Based on Business Administration Data},
        proceedings={Application of Big Data, Blockchain, and Internet of Things for Education Informatization. Second EAI International Conference, BigIoT-EDU 2022, Virtual Event, July 29--31, 2022, Proceedings, Part I},
        proceedings_a={BIGIOT-EDU},
        year={2023},
        month={1},
        keywords={Business administration Data mining Data analysis},
        doi={10.1007/978-3-031-23950-2_42}
    }
    
  • Pengfei Ma
    Year: 2023
    Data Mining Analysis Based on Business Administration Data
    BIGIOT-EDU
    Springer
    DOI: 10.1007/978-3-031-23950-2_42
Pengfei Ma1,*
  • 1: Nanchang Institute of Technology
*Contact email: 416930145@qq.com

Abstract

With the advent of the era of big data, the utilization value of data has been paid more and more attention by various industries. Data mining shows its superiority in the secondary utilization of existing data, which can produce great economic benefits to our life. In order to improve management efficiency and adapt to modern management, the industrial and commercial administration department has gradually established its own business management system and realized the digitization of economic household registration. However, its current business system can only provide daily transaction management. It is becoming more and more difficult to obtain useful information from the business system, which seriously affects the full utilization of data. Therefore, based on the data mining of business administration data, this paper makes an in-depth understanding and analysis of business administration data.

Keywords
Business administration Data mining Data analysis
Published
2023-01-12
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-23950-2_42
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