With the rapid increase of data volume in operation, the application of data mining technology in operation optimization is becoming increasingly widespread. This article analyzes several core data mining techniques, including classification and regression analysis, association rule exploration, anomaly detection and prediction algorithms, as well as the application of deep learning and artificial intelligence. Through in-depth research on these technological features and application scenarios, the actual effects and application value in multiple operational improvement areas such as sales forecasting, inventory control, risk assessment, and customized recommendations have been revealed. Data mining technology not only improves operational efficiency, but also provides data support for enterprise strategy decisions, making it an indispensable tool for modern enterprise management.

Xinran Tu. Data Mining Techniques and Their Practical Applications in Operational Optimization. Socio-Economic Statistics Research (2025), Vol. 6, Issue 2: 144-152. https://doi.org/10.38007/SESR.2025.060215.

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