Construction of enterprise business management analysis framework based on big data technology

Area of Science:

• Business Management
• Data Science
• Operations Research

Background:

• Traditional enterprise management relies heavily on human resources, leading to unstable outcomes due to subjective factors.
• The increasing complexity of the business environment necessitates more scientific and data-driven management approaches.

Purpose of the Study:

• To design an enterprise business management system leveraging intelligent data technology.
• To construct a framework for analyzing enterprise business management.
• To improve the efficiency and scientific basis of various management functions.

Main Methods:

• Development of an enterprise business management system integrating intelligent data technology.
• Construction of an enterprise business management analysis framework.
• Application of an improved C4.5 algorithm for optimization.

Main Results:

• The proposed system aids managers in optimal planning, enhancing production, sales, financial, and personnel management.
• The improved C4.5 algorithm demonstrated significant reductions in shipping fuel costs for Company A, totaling 13349.09 yuan across five voyages.
• The optimized ship speed management effectively lowered operational expenses and boosted profits.

Conclusions:

• The improved C4.5 algorithm offers higher accuracy and better time efficiency than traditional methods.
• Decision tree-based algorithms are feasible for enterprise business management systems, providing effective decision support.
• Intelligent data technology enhances the scientific basis and efficiency of enterprise management.