Developing the digital economy, improving construction of big datasets and innovating applications of big data in various industries have become a national strategy. The development level and policy tendency of regional strategies directly affect the construction and application of big data relating to agriculture. An investigation and analysis of the current situation regarding regional big data and agricultural big data in 2020 enables a comparative evaluation index system to be developed. The development of regional big data and the construction level of regional agricultural big data are compared horizontally, and then the connotation and correlation of various indicators in each region are compared vertically. A three-dimensional analysis focusing on the level of regional economic development, regional infrastructure, regional policies, talent construction, capital investment, and industrial agglomeration is also conducted. It’s unbalanced when it comes to the development level of regional big data and the construction of regional agricultural big data in China, which is higher in the east while lower in the west. The environmental development index has a significant impact on the development level of big data and agricultural big data. The process of constructing data resources varies among regions, and public data are not readily available in many provinces. Regional competition leads to the concentration of talent, organizations, and enterprises, and investment in scientific research has suppressed innovation in central, western, and northeast provinces. Different provinces put different levels of energy into the construction of regional agricultural big data. In addition to that, the complexity of agricultural data means that the construction process lags behind that of regional big data. Therefore, there are contradictions between the construction of agricultural big data in some regions and the development level of the economy and regional big data, meaning that development strategies cannot be effectively implemented. This has become a bottleneck for the development of regional big data and seriously hinders the development of regional/national big data and agricultural big data. This paper further summarizes the problems in the implementation of big data and agricultural big data strategies, and discusses appropriate development strategies for big data and agricultural big data.