Using Big Data Analysis to Optimize the Financing Structure and Capital Allocation of Energy Enterprises
DOI:
https://doi.org/10.71222/95bjdv97Keywords:
big data analysis, energy enterprise, financing structure, capital allocation, risk early warning systemAbstract
With the gradual development of big data technology, the application of big data technology has a certain impact on the financing structure and capital allocation of energy enterprises. Through data integration, the information big data platform establishes an intelligent data analysis model, which can more effectively optimize financing methods, accurately position investment directions, and promptly determine the location of investment risks. This paper aims at the problems of concentrated funds, investment deviation and low risk awareness of current energy enterprises, and proposes a big data aggregation approach to solve them, in order to improve the effectiveness of the company's financial management, achieve the goal of structural adjustment.
References
1. K. Sravanthi, and T. S. Reddy, "Applications of big data in various fields," International Journal of Computer Science and Information Technologies, vol. 6, no. 5, pp. 4629-4632, 2015.
2. Y. Zhang, "Financial Optimization Budget Allocation Model Based On Big Data and Data-Driven Technology," Procedia Computer Science, vol. 247, pp. 396-402, 2024. doi: 10.1016/j.procs.2024.10.047
3. S. Ren, "Optimization of enterprise financial management and decisionmaking systems based on big data," Journal of Mathematics, vol. 2022, no. 1, p. 1708506, 2022. doi: 10.1155/2022/1708506
4. W. Wang, Q. Li, and F. Zhu, "Enterprise intelligent manufacturing data analysis technology based on big data analysis," International Journal for Simulation and Multidisciplinary Design Optimization, vol. 15, p. 5, 2024. doi: 10.1051/smdo/2024005
5. D. Wang, and J. U. Abellera, "Research on optimization strategies for cash flow management of small and micro enterprises based on big data analysis," In AIP Conference Proceedings, December, 2024, p. 050038. doi: 10.1063/5.0223380







