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The Application of Big Data in Cost Control and Budgeting of Power Financial Management

In: Proceedings of the 2025 7th International Conference on Economic Management and Model Engineering (ICEMME 2025)

Author

Listed:
  • Jinxiu Zhang

    (State Grid Gansu Electric Power Company)

  • Zhipeng Li

    (State Grid Gansu Electric Power Company)

  • Shuo Shen

    (State Grid Gansu Electric Power Company)

  • Yixuan Chen

    (State Grid Gansu Electric Power Company)

  • Jun Wang

    (State Grid Gansu Electric Power Company)

Abstract

This article explores the application of big data in cost control and budgeting in power financial management. Firstly, it elaborates on the role of big data technology in financial management of power enterprises, and points out the need to build a financial center database with multiple modules to mine and integrate data through cloud computing to improve management efficiency; Next, explain the process of constructing a financial decision-making model for enterprises, including data preprocessing, Bayesian network structure learning based on K2 algorithm, parameter learning, and post correction mechanism; Finally, a comparative experiment was conducted using a certain power enterprise as a case study, and the results showed that the financial decision support model based on post modified Bayesian networks can more effectively reduce enterprise costs, improve profits, optimize asset liability ratios, and provide scientific support for financial cost control and budgeting in power enterprises compared to the other two methods.

Suggested Citation

  • Jinxiu Zhang & Zhipeng Li & Shuo Shen & Yixuan Chen & Jun Wang, 2026. "The Application of Big Data in Cost Control and Budgeting of Power Financial Management," Advances in Economics, Business and Management Research, in: Touria Benazzouz & Sandeep Saxena & Hui Nee Au Yong & Nor Zafir Md Salleh (ed.), Proceedings of the 2025 7th International Conference on Economic Management and Model Engineering (ICEMME 2025), pages 39-47, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6239-602-9_5
    DOI: 10.2991/978-94-6239-602-9_5
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