By systematically summarizing the development process of sintering technology, based on the research on the application of big data technology in the process of intelligent sintering, the intelligent sintering technology is summarized and analyzed from such three aspects as sintering data preprocessing, key parameter prediction of sintering, and key parameter evaluation and optimization of sintering. In terms of sintering data preprocessing, in view of such problems as missing data, abnormal values, different data dimensions and feature redundancy, the data problems and algorithm characteristics should be comprehensively considered, and such appropriate methods as imputing missing values, handling outliers, data normalization, and feature extraction should be adopted to improve the data quality and credibility. In the prediction of key parameters of sintering, it is necessary to combine big data technology and sintering process theory, deep learning and ensemble learning intelligent algorithms are used to establish the prediction model of sintering parameters to improve the accuracy and precision of the model. In terms of sintering parameter evaluation and optimal control, based on the integration of sintering process data information and sintering process mechanism, a multi-objective collaborative optimization model of sintering process is established by sampling machine learning method to realize the evaluation and optimization control of sintering process parameters. Based on the development of a new generation of big data technology and artificial intelligence technology, the future research direction and development prospect of sintering intelligent system are further prospected.