Big Data Theory of Industrial Supply Chain Based on Complex Information Integration

The development of big data provides a more adequate foundation for the management and construction of traditional industrial supply chain finance. This article discusses the research on big data theory in industrial supply chains based on complex information integration. This paper proposes and designs a big data system for the common industry supply chain. The whole system architecture is comprised of: platform support layer, data resource layer, data processing layer, internal business layer and public service layer. The platform support layer provides public services for financial big data, and addresses all problems related to infrastructure, hardware resources, and software environment. The data resource layer is used for the management of the list of rights and responsibilities and the list of events. The data processing layer can transform the information into understandable knowledge. The internal business layer is logically isolated from the Internet to ensure information security. The operation module of the supply chain industry standardizes the interface between logistics, the supply chain management system and related collaborative supervision system. Based on this, the research on complex information integration of industrial supply chain is carried out to improve the parallel processing efficiency of big data. Through complex information integration, the parallel processing efficiency of big data in industrial supply chain has increased by 76%, the execution time is short, and the alignment performance is better. The results show that the system designed in this paper can reasonably develop the data resources in the online supply chain and improve the parallel processing efficiency of big data in the industrial supply chain. © 2024 CRL Publishing Ltd.