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Construction of enterprise business management analysis framework based on big data technology

With the development of science and technology, people have added a new concept big data, which is the most concerned topic at present, and has also brought great changes to the business management environment of enterprises. At present, most of the business administration work of enterprises is mai...

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Detalles Bibliográficos
Autores principales: Peng, Jinqian, Bao, Liyuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10293672/
https://www.ncbi.nlm.nih.gov/pubmed/37383204
http://dx.doi.org/10.1016/j.heliyon.2023.e17144
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author Peng, Jinqian
Bao, Liyuan
author_facet Peng, Jinqian
Bao, Liyuan
author_sort Peng, Jinqian
collection PubMed
description With the development of science and technology, people have added a new concept big data, which is the most concerned topic at present, and has also brought great changes to the business management environment of enterprises. At present, most of the business administration work of enterprises is mainly based on human resources, and the enterprise activities are managed through the professional knowledge of relevant management personnel. However, due to human subjective factors, the management effect is unstable. Therefore, this paper designed an enterprise business management system based on intelligent data technology, and constructs an enterprise business management analysis framework. The system can help managers to make the best plan when implementing management measures, improve the efficiency of production management, sales management, financial management, personnel organization structure management, etc., so as to make business management more scientific. The experimental results showed that the improved C4.5 algorithm in the business management system proposed in this paper reduced the fuel consumption cost of shipping company A by 220.21 yuan at least and 11050.12 yuan at most, which reduced the fuel consumption cost of the company's five voyages by 13349.09 yuan in total. This indicates that the improved C4.5 algorithm has higher accuracy and better time efficiency compared to traditional C4.5 algorithms. At the same time, the optimized ship speed management effectively reduces the fuel consumption cost of flights and improves the company's operating profit. The article proves the feasibility of improved algorithms based on decision trees in enterprise business management systems, and has a good decision support effect.
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spelling pubmed-102936722023-06-28 Construction of enterprise business management analysis framework based on big data technology Peng, Jinqian Bao, Liyuan Heliyon Research Article With the development of science and technology, people have added a new concept big data, which is the most concerned topic at present, and has also brought great changes to the business management environment of enterprises. At present, most of the business administration work of enterprises is mainly based on human resources, and the enterprise activities are managed through the professional knowledge of relevant management personnel. However, due to human subjective factors, the management effect is unstable. Therefore, this paper designed an enterprise business management system based on intelligent data technology, and constructs an enterprise business management analysis framework. The system can help managers to make the best plan when implementing management measures, improve the efficiency of production management, sales management, financial management, personnel organization structure management, etc., so as to make business management more scientific. The experimental results showed that the improved C4.5 algorithm in the business management system proposed in this paper reduced the fuel consumption cost of shipping company A by 220.21 yuan at least and 11050.12 yuan at most, which reduced the fuel consumption cost of the company's five voyages by 13349.09 yuan in total. This indicates that the improved C4.5 algorithm has higher accuracy and better time efficiency compared to traditional C4.5 algorithms. At the same time, the optimized ship speed management effectively reduces the fuel consumption cost of flights and improves the company's operating profit. The article proves the feasibility of improved algorithms based on decision trees in enterprise business management systems, and has a good decision support effect. Elsevier 2023-06-11 /pmc/articles/PMC10293672/ /pubmed/37383204 http://dx.doi.org/10.1016/j.heliyon.2023.e17144 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Peng, Jinqian
Bao, Liyuan
Construction of enterprise business management analysis framework based on big data technology
title Construction of enterprise business management analysis framework based on big data technology
title_full Construction of enterprise business management analysis framework based on big data technology
title_fullStr Construction of enterprise business management analysis framework based on big data technology
title_full_unstemmed Construction of enterprise business management analysis framework based on big data technology
title_short Construction of enterprise business management analysis framework based on big data technology
title_sort construction of enterprise business management analysis framework based on big data technology
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10293672/
https://www.ncbi.nlm.nih.gov/pubmed/37383204
http://dx.doi.org/10.1016/j.heliyon.2023.e17144
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