Enterprise Financial Accounting Information Management System based on Big Data Mining

Enterprise financial accounting, in the face of distributed and heterogeneous financial accounting data, effective aggregation and mining for data-driven management decisions are important means for fine-grained enterprise control. This paper studies the method of constructing an intelligent management system for enterprise financial accounting based on the concept of big data. First, the business process is analyzed to clarify data collection interfaces and quality control mechanisms. Then, time series analysis, association rules, and machine learning prediction algorithms are integrated to establish analytical models that match business objectives. Based on this, a process-oriented and service-oriented system framework is designed to achieve unified integrated access to multi-source data and model analysis services. Experiments show that the system can effectively discover relationships between data and time series change patterns, perform sales forecasting, anomaly detection, and more, demonstrating its support in practical procurement planning and marketing decisions, validating the effectiveness of the system design. This research provides a positive practical exploration for the construction of an intelligent enterprise financial accounting management system.