Data elements serve as a crucial driver for intelligent aerospace manufacturing.This paper proposes a comprehensive data integration framework tailored to the needs of heterogeneous data integration and optimization in the manufacturing of complex aerospace components，including the key techniques such as data acquisition，data processing and modeling，and data analysis and optimization.In response to the spatio-temporal coupling characteristics of multi-source heterogeneous data in the whole process of aerospace manufacturing，a manufacturing data fusion system is proposed to improve the data processing efficiency and integration capabilities such as multi-dimensional index modeling，multi-scale data alignment，and time-scale transformation.Regarding the complex operating laws contained in the aerospace manufacturing process，an algorithm based on the relational network model and graph neural network deconvolution is proposed to enhance the analysis ability of the manufacturing process.Finally，typical application scenarios of data analysis in aerospace intelligent manufacturing are presented，along with case studies that validate the effectiveness of the methods proposed in the paper.