s:Based on the data of A-share listed companies in Shanghai and Shenzhen from 2012 to 2022 to measure the level of new quality productivity of enterprises (NQP), a multi-period difference-in-differences model is constructed to study the impact of data factor agglomeration on the new quality productivity of enterprises with the national-level big data comprehensive experimental zone as a quasi-natural experiment. The study shows that data factor agglomeration promotes the development of new quality productivity of enterprises, and this conclusion still holds after PSM-DID, placebo test and other robustness tests. Data factor agglomeration can empower the development of firms" new quality productivity by improving human capital level and promoting green technology innovation; with the increase of industry competition and media attention, the driving effect of data factor agglomeration on firms" new quality productivity increases. The effect of data factor agglomeration on the new productivity of enterprises is more significant in non-state-owned enterprises, high-tech industries, and regions with better digital infrastructure. Further research suggests that new productivity can contribute to high-quality development of enterprises and that this effect is sustainable. The findings provide insights into how new factors of production can be utilized to foster NQP and how to understand the "causes and consequences" of NQP development.