Research on Data Classification and Grading Method Based on After sales Energy Replenishment Scenarios

Data security is the foundation of data opening, circulation, integration and application. At present, the data security system still needs to be improved in practice, and the classification and grading standards mainly focus on the external influence of data, ignoring the intrinsic value of data. In this paper, on the basis of traditional classification and grading, supplementary value evaluation indicators are added to correct the data grade. Taking the after-sales energy supplement scenario of new energy as an example, on the basis of determining the importance between indicators through expert scoring method, iterative adjustment is carried out on the basis of consistency test and concentration adjustment test based on Kendall coefficient, and finally the weight of each indicator is obtained, which provides a reference method for the data classification and grading of after-sales energy supplement scenario and even automobile industry.