As a new type of production factor in the digital economy era, data is highly compatible with the connotation of new-quality agricultural productive forces and represents a key driver of innovation and future development in agricultural productivity. Exploring how data factorization drives the development of new-quality agricultural productive forces is of great theoretical and practical significance for promoting high-quality agricultural development and accelerating agricultural modernization. Based on panel data from 30 Chinese provinces (autonomous regions and municipalities) spanning from 2012 to 2022, this study constructs a multiple regression model to examine the impact effects and transmission mechanisms of data factorization on the development of new-quality agricultural productive forces. The results show that data factorization significantly promotes the development of new-quality agricultural productive forces, and this conclusion remains robust after replacing the measurement of core variables, conducting placebo tests, and applying instrumental variable and SYS-GMM methods. Heterogeneity analysis indicates that the promoting effect of data factorization is weaker in western regions than in other regions, and that its impact on major grain-producing areas is greater than that on non-grain-producing areas. In terms of transmission mechanisms, data factorization advances new-quality agricultural productive forces by fostering agricultural technological progress and improving agricultural technical efficiency, with the mediating effect of technical efficiency exceeding that of technological progress. Overall, the findings confirm that data factorization plays a significant role in driving the development of new-quality agricultural productive forces, providing empirical evidence for cultivating such forces through data elements and accelerating agricultural modernization in the digital economy era.