Abstract:With the rapid increase of the power grid data, the traditional data mining and analysis methods cannot meet the requirements of smart grid, and the big data analysis provides corresponding means to achieve this. This paper first introduces the theory and technology of the big data. From the point of view of the status of power transmission and transformation equipment and the application of the specific power grid business, data integration, data storage, data calculation, data analysis and visualization of results of five parts are carried out. Then according to the transmission equipment historical defect data and the problem data of the whole technical supervision process, the application of principal component analysis and clustering algorithm, the construction characteristics of transformer equipment defect analysis model, the equipment defect content classification features labeling, transport inspection personnel to provide relevant grid data analysis for decision making; finally introduced the prospect to carry out the latent fault prediction of the power transmission equipment.