[Objective]In order to provide references for computational innovations, an industrial needs driven integration platform for big data and artificial intelligence analysis and application is proposed to promote the traditional industry intelligence and intelligent technology industrialization. [Methods]Based on the integration of both data feature understanding and platform requirements in industry-oriented application scenarios, the application-driven platform hierarchy in supercomputer center is designed in a fused architecture consists of supercomputing, big data, cloud computing, artificial intelligence and internet of things, which contains implications on physical facilities, system software and management system. In the supercomputer center, it mainly integrates service-related hardware facilities for big data, super-computing and cloud computing to realize data sharing, high-performance processing, and data security control. By eliminating the difference between various data sources, the platform provides an unified standard data access interface for upper-layer applications, which promotes standardization of big data processing in related industries for resource and data sharing. As an important field of big data applications, the high-efficiency big data application platform for industrials combines with the industrial cloud platform to realize data collection, transmission, collaboration and application by integrating the physical device, virtual network and big data analysis methods. The characteristics of industrial-based big data and artificial intelligence require innovative applications that support the production tasks, such as design, production, sales, operation and maintenance. [Results]Based on the platform, it has achieved typical applications in industrial fields such as equipment manufacturing, networked vehicles, medical health, etc., showing good applicability. In manufacturing, the platform is a tool for product supplier quality management control, carrying out abnormal inspection and prediction of parts and components, and achieving management ability to control the entire product chain. In networked vehicle, by collecting vehicle driving data and using deep learning modeling, it is possible to analyze the safety of autonomous driving and driving behavior. In disease screening, big data and artificial intelligence analysis for radiological imaging, pathology images, and electronic medical records can help doctors complete analysis of repetitive tasks and complex tasks. [Limitations]As a public open platform to provide services, institutional credibility and data security are important issue to be solved in the next step. [Conclusions]Application-driven big data and artificial intelligence integration platform acts as an important part of social development and government-controllable intelligent industry science development ecology, which further solves the practical problems that insufficient innovation ability in China's intelligent industry.