In the process of intelligent coal mine construction in our country produces massive data, including the data produced by ventilation, gas and other kinds of monitoring and monitoring system are dynamic real-time data, data scale is huge, and directly reflect the safety of coal mine production, for this part of monitoring and monitoring data, if analyzed and applied well, can greatly improve the level of safety production of intelligent coal mine. Therefore, it is an important task for the high-quality development and digital transformation of the coal industry to explore the path to improve the ability of coal mine monitoring data governance. Based on the characteristics of data elements and application paradigm of coal mine monitoring and control, this paper analyzes the role and position of data governance in intelligent coal mine enterprises, defines the concept and connotation of intelligent coal mine monitoring and control data governance, and puts forward the research paradigm and overall framework of data governance in the whole process from basic data collection, data development and management to data value formation. Following the concept of data-driven decision-making, the quantitative relationship and logical relationship implicit in intelligent coal mine monitoring data are identified, and multiple comprehensive research methods and deduction methods such as big data tools and management decision-making methods are adopted to mine laws, rules, patterns and mechanisms, so as to guide data application practice with theories. A data value realization path of "information mining- theory inference-scene application" is formed, and a structural equation theoretical model of monitoring and monitoring data governance ability improvement path is constructed, and the demand-oriented, transfer and influence relationship between learning elements and learning modes of monitoring and monitoring data governance ability improvement under the background of intelligent coal mine construction is systematically analyzed. This paper explores the key path to improve the monitoring data governance ability of coal enterprises.