Proceedings of the 2022 2nd International Conference on Business Administration and Data Science (BADS 2022)

Enterprise Information Product Configuration Management System Based on Data Analysis Algorithm

Authors
Haiqi Xu1, *, Suqiong Ge1, Fei Xiao1
1The Eighth Reaserch Institute, China State Shipbuilding Corporation, Nanjing, 210003, Jiangsu, China
*Corresponding author. Email: 76549864@qq.com
Corresponding Author
Haiqi Xu
Available Online 29 December 2022.
DOI
10.2991/978-94-6463-102-9_115How to use a DOI?
Keywords
Data Analysis Algorithm; Clustering Algorithm; Information Product; Configuration Management
Abstract

With the popularization of computer in the process of enterprise informatization product configuration management, product information of various types, informatization and strong dynamic has been formed. In order to effectively integrate, organize and manage this information, it is very important to develop product information configuration management technology. In order to solve the shortcomings of enterprise information product configuration management research, on the basis of discussing the functional equations of enterprise product configuration management and data analysis clustering algorithm, this paper aims at the application of enterprise information product configuration management system based on data analysis algorithm. Development tools and runtime environment are briefly introduced. And design and discuss the software materialization results and product project management process of enterprise information product configuration management based on data analysis algorithm. Finally, based on the four algorithms in data analysis algorithm, the calculation time of product classification in enterprise information product configuration management system is carried out. The experimental comparison and analysis, the test results show that the four algorithms in the data analysis algorithm have short calculation time and good stability for the classification of the four information products in the enterprise information product configuration management system. The data analysis algorithm used in this paper The computing time of the clustering algorithm in 2 is shorter, and the computing time of the four product classifications is between 16s-20s, while the computing time of the other three algorithms is stable in the range of 50s-70s. Therefore, the reliability of the enterprise information product configuration management system based on the data analysis algorithm is verified.

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.

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Volume Title
Proceedings of the 2022 2nd International Conference on Business Administration and Data Science (BADS 2022)
Series
Atlantis Highlights in Computer Sciences
Publication Date
29 December 2022
ISBN
10.2991/978-94-6463-102-9_115
ISSN
2589-4900
DOI
10.2991/978-94-6463-102-9_115How to use a DOI?
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  - Haiqi Xu
AU  - Suqiong Ge
AU  - Fei Xiao
PY  - 2022
DA  - 2022/12/29
TI  - Enterprise Information Product Configuration Management System Based on Data Analysis Algorithm
BT  - Proceedings of the 2022 2nd International Conference on Business Administration and Data Science (BADS 2022)
PB  - Atlantis Press
SP  - 1114
EP  - 1122
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-102-9_115
DO  - 10.2991/978-94-6463-102-9_115
ID  - Xu2022
ER  -