In today’s rapid development of information technology, the big data industry has ushered in explosive growth, and big data analysis has become an important research topic in the cross-cutting field of computing. This study constructs a big data prediction base model based on deep learning, and uses the improved butterfly optimization algorithm with OGRU model to realize feature selection and classification processing of big data. Then the Adam algorithm is used to optimize the parameters of the model, and finally the classification and prediction model of big data based on deep learning is constructed. Simulation and empirical analysis results show that the model proposed in this paper has excellent classification and prediction performance, and can meet the efficiency requirements of big data classification and prediction. The prediction errors of distribution network load data and smart charging pile operation data are lower than 9% and 16%, respectively, which have high practical application value. This study is of great significance to the research related to big data classification and prediction in different fields, and provides an effective method for data prediction in complex scenarios such as industrial as well as power grid scheduling.