Aiming at the problems of multi-source heterogeneous data processing difficulties and weak knowledge relevance in informatization equipment management, traditional equipment management methods find it difficult to use data to assist decision-making efficiently. Effectively managing data and updating knowledge promptly is a huge challenge today. This paper combines top-down and bottom-up methods to construct the knowledge graph of informatization equipment management, applies the clustering method based on the calculation of text similarity for entity alignment, uses the incremental updating strategy to update the knowledge graph, and explores the value of the application of the knowledge graph of informatization equipment management. This method can effectively integrate equipment life cycle data, realize knowledge association mining and intelligent services, and provide more efficient and accurate solutions for informatization equipment management.