Abstract: Hidden danger investigation and governance are the top priority of coal mine enterprise's safety management. With the development of informatization, coal enterprises have accumulated a lot of hidden danger data. How to effectively use these historical data has become a new challenge of current safety informatization construction in coal enterprises. This paper first puts forward the concept of data cube and OLAM architecture, and then proposes Apriori_DataCube algorithm based on the integration of OLAP drill function and inter-dimensional association rule. Secondly, this paper extends support-confidence framework based on Kulczynski. Finally, this paper empirically analyzes the Xuehu mine hidden historical data provided by Microsoft SQL Server integration service platform, which provides a new way for coal mine enterprise to grasp the hidden danger trends timely and enhance the hidden danger investigation and governance ability.

Key words: mine safety, hidden danger trends, OLAM, drill, inter-dimensional association rule, Kulczynski, SSIS