The prediction of the scale of big data talent training in colleges and universities belongs to an important content in the field of big data talent research in colleges and universities. The article uses the primary exponential smoothing method in the time series and the gray model prediction method to predict the scale of college big data talent training and talent demand respectively, and then uses the Lorenz curve and the Gini coefficient to study the matching degree of education in the field of big data. There are experimental results can be obtained, the degree of matching between the professional settings of colleges and universities and the trend of the demand for big data-related positions in enterprises needs to be strengthened, in order to adapt to the future demand for big data-related positions in enterprises, and to further output talents that are in line with the enterprises, the article proposes a model of big data talent cultivation civic and political education in colleges and universities based on the KSAO model. Based on the KSAO model, the ideological education mode of big data talent cultivation in colleges and universities can be implemented at six levels: “theory + project” curriculum system, promoting the dual strategy of “on-campus simulation + off-campus practice”, establishing the KSAO multi-dimensional practice assessment system, strengthening the coordination of the industry-teaching cooperation model, building a cloud learning platform with the help of information technology, and implementing the top-down education design.