Due to the complex relationship between indicators in data,traditional mathe-matical statistical methods can no longer meet the demand,and many practical problems put forward higher requirements for data processing.In order to analyze those characteristics of complex data such as its high dimensions and indicators correlation between complex,group effect,this paper put forward its own remarkable complex data processing scheme:through the analysis of the correlation of data between various indicators,find out the several variables which have effect of group composition variables cluster,we call it for granule,in order to ef-fectively find the granules,this paper proposed GC,and find several indicators which have effect of group team.After the discovery of the granules,we obtained the kernel variables re-flecting the characteristics of the aggregates by analyzing the correlation between the internal indicators of the granules.Examples are given to show that the discovery of granules and the structural analysis of granules can effectively analyze the correlation between complex data indicators.
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