An enhanced cascading failure model integrating data mining technique is proposed in this paper. In order to better simulate the process of cascading failure propagation and further analyze the relationship between failure chains, in view of a basic framework of cascading failure described in this paper, some significant improvements in emerging prevention and control measures, the subsequent failure search strategy as well as the statistical analysis for the failure chains are made elaborately. Especially, a sequential pattern mining model is employed to find out the association pertinent to the obtained failure chains. In addition, a cluster analysis model is applied to evaluate the relationship between the intermediate data and the consequence of obtained failure chain, which can provide the prediction in potential propagation path of cascading failure to reduce the risk of catastrophic events. Finally, the case studies are conducted on the IEEE 10-machine-39-bus test system as benchmark to demonstrate the validity and effectiveness of the proposed enhanced cascading failure model. Some preliminary concluding remarks and comments are drawn.