Abstract: The quality deterioration degree of modern brick-wood houses in Shanghai is affected by various factors and involves a large amount of data. Since indicators are ordered categorical variables, and there is a correlation between them, the principal component analysis method and the weighting method of complex correlation coefficient in the big data analysis technology were applied to quantitatively evaluate the quality deterioration of the modern brick-wood houses in Shanghai, so as to improve the accuracy of evaluation results. Firstly, material strength and component damage were selected as the evaluation indicators of the quality deterioration of the houses. On this basis, the principal component analysis method and the weighting method of the complex correlation coefficient were used to analyze the data of evaluation indicators, and the final evaluation results were obtained. As a result, the quality deterioration of the modern brick-wood houses in Shanghai was evaluated. The evaluation results of an engineering example show that the evaluation values of the principal component analysis method and the weighting method of the complex correlation coefficient are relatively close, and they are consistent with the actual measured results, which confirms the feasibility of the two methods.