This paper aims to study how to innovate and develop the culture of the old industrial base of Northeast China in the environment of big data. In this paper, based on sorting out the big data processing process, a data mining model based on the Bayesian network is established, parameter learning is performed using great likelihood estimation, and the Bayes-Dilley scoring function is obtained by structure learning. Then, based on the trained network, the big data mining analysis is performed on the cultural industry of the old industrial base of northeast China and the northeast China cultural impression words on social networks. From 2018 to 2021, the successive annual growth values of the cultural industry of the old industrial base of northeast China are 119.835 billion yuan, 120.345 billion yuan, 115.764 billion yuan, 116.001 billion yuan, and the proportion of GDP increased from 2.11% raised to 2.38%. Among them, Jilin was raised from 2.14% to 2.46%, Heilongjiang from 2.65% to 2.72%, and Liaoning from 1.03% to 1.52%. The cultural innovation of the old industrial base in Northeast China under the environment of big data should abandon the traditional culture, find the cultural positioning, break through the thinking stereotype, create a new advanced culture, and change the ideology.