Research on the Application of Multidimensional Statistical Analysis in Complex Data Processing

Abstract

With the continuous expansion of data scale and the increasingly complex data structure, how to effectively process and analyze complex data and mine valuable information contained in it has become an important research topic. This paper discusses the application of multidimensional statistical analysis in complex data processing, focusing on the advantages of principal component analysis (PCA) in dimensionality reduction and revealing the internal structure of data. Based on the consumer transaction records of an e-commerce platform in 2023, the study reduced the 15-dimensional original data to a low-dimensional space through PCA, and the cumulative variance contribution rate reached 88.5%. The results show that PCA can effectively simplify the data structure, reveal the key dimensions of consumer behavior, such as consumption ability and consumption tendency, and provide strong support for the formulation of accurate marketing strategies.