Every technological advance in the development of human society will lead to a series of new products and services, but at the same time, it will lead to a sharp increase in the consumption of resources and energy. Although the progress of technology has improved the efficiency of resource and energy use, the development mode of increasing per capita energy consumption is not sustainable. In addition to the supply side of energy efficiency, a reasonable guide to demand side can be the key used to achieve building energy efficiency. To achieve the change of building energy-saving mode from the supply side to the demand side, we must properly describe the energy by using characteristics in a specific indoor environment, and assess the reasonableness of building energy consumption from the demand side, then identify accurately the reason of energy waste. Along with the rapid development of building automation system and IOT technology, a large amount of building energy consumption data with specific indoor environment features are acquired, then we can use data mining technology to extract energy saving clues and strategies from these low density value building daily operation data. This paper briefly introduces the data mining technology, and summarizes the application of various mining methods in building energy saving, and prospects of its development trend.