Research on the Transformation Path of Financial Informatization in Electric Power Enterprises Driven by Big Data
- DOI
- 10.2991/978-94-6239-640-1_13How to use a DOI?
- Keywords
- big data; Electric power companies; Financial informatization; Transformation path; Financial Data Management System
- Abstract
This article focuses on the transformation path of financial informatization in power enterprises driven by big data. In response to the problems of inefficient data processing, single analysis, and lagging risk response in traditional financial models under the intensification of digitalization in the energy industry and competition in the power market, a multi-level financial data management system including data source layer, storage layer, processing layer, etc. is proposed to be constructed. The system integrates ETL, Hadoop, Canopy Ant Colony K-Means and other technologies to achieve full process intelligence of financial data. It has been verified through a provincial power enterprise instance and has achieved significant results in material settlement efficiency and cost accounting accuracy, providing support for power enterprises to break through financial bottlenecks and achieve financial and business collaboration.
- Copyright
- © 2026 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 - Xuan Zhou AU - Fei Han AU - Yi Zhang AU - Wanlong Huang AU - Yifei Tang PY - 2026 DA - 2026/04/20 TI - Research on the Transformation Path of Financial Informatization in Electric Power Enterprises Driven by Big Data BT - Proceedings of the 2026 5th International Conference on Big Data Economy and Digital Management (BDEDM 2026) PB - Atlantis Press SP - 147 EP - 154 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6239-640-1_13 DO - 10.2991/978-94-6239-640-1_13 ID - Zhou2026 ER -