The digital economy is the future development direction of the global economy, and it is becoming a key force in reorganizing global factor resources, reshaping the global economic structure, and changing the pattern of global competition. However, the development of the digital economy is affected by a variety of factors. In this paper, we mainly use data mining methods to quantify and cluster analyze technological innovation and digital economic development, and analyze the influencing factors of digital economic development by combining statistical models. According to the results of empirical analysis, it is found that the regression coefficient of the total number of patents is 0.0125, which is significantly correlated at the level of 1%, indicating that every 1 unit increase in the total number of patents will lead to a 0.0125 unit increase in the level of digital economy. Overall, the number of patent citations plays a smaller role in the development of the digital economy, with a regression coefficient of 0.0123, and utility model patents have the greatest role in promoting the digital economy. Data mining technology can fully analyze the deep relationship between indicator variables and improve the quality of quantitative analysis in technological innovation and digital economic development.