As a crucial management tool for enterprises to coordinate resource allocation and achieve strategic objectives, comprehensive budget management has seen increasing limitations in its traditional operational methods—particularly in data foundation, forecasting accuracy, execution monitoring, and evaluation—against the dual backdrop of heightened operational uncertainty and accelerated digital transformation. Big data, characterized by massive volume, diverse types, rapid access, and high application value, provides technical support for budget management through multi-source data integration, intelligent forecasting, real-time monitoring, and multi-dimensional analysis. Based on a review of relevant theories and policies on big data and comprehensive budget management, this paper analyzes the mechanism of big data's empowerment in comprehensive budget management from a closed-loop perspective encompassing budget formulation, execution, analysis, and evaluation. It identifies practical challenges in enterprises regarding data foundation, formulation methods, execution monitoring, and assessment criteria. Subsequently, it proposes optimization pathways such as building a budget data hub, introducing intelligent forecasting models, advancing business-finance integration and dynamic monitoring, expanding multi-dimensional analysis and performance evaluation, strengthening organizational safeguards, and enhancing data governance. These recommendations aim to provide insights for improving the efficiency and effectiveness of comprehensive budget management in the big data era.

Mengya Shen. Research on Optimizing Enterprise Comprehensive Budget Management with Big Data Empowerment. Academic Journal of Business & Management (2026), Vol. 8, Issue 10: 67-72. https://doi.org/10.25236/AJBM.2026.081009.

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