The architecture of traditional clothing information detection system has defects, which makes it unreliable. In view of this, this study creates a new clothing information detection system based on data analysis. This paper adopts the method of layering and module division to construct the system architecture, and divides the system into data acquisition layer, data preprocessing layer, feature extraction layer and decision layer. In the data acquisition layer, various sensors are used to collect various types of clothing information. The data preprocessing layer uses data cleaning technology to remove outliers, and uses data normalization methods to unify data of different scales. The feature extraction layer extracts the key features of clothing from the preprocessed data. The decision layer makes the final judgment and decision based on the extracted features. A rule-based decision tree is used. When building a decision tree, decision rules are set according to the style, size, fabric and other characteristics of clothing. A distributed architecture is used in the study to improve the processing power and fault tolerance of the system, and different functional modules are distributed to multiple computing nodes. In the implementation process, the Apache Spark distributed computing framework is selected to assign camera acquisition tasks at different locations to different edge computing nodes to collect clothing information in parallel. At the same time, a redundant architecture is set to ensure system reliability, and main modules and backup modules are set for key functional modules such as the decision module of the decision layer. The average value of the system in terms of detection accuracy is about 97.89%, which is about 6.02 percentage points higher than that of traditional systems; in terms of detection failure rate, the system in this paper is less than 0.15% in 10 of the 15 comparisons, which is much lower than the traditional system. The system has created an efficient, stable and reliable information detection platform for the clothing industry, helping enterprises to achieve digital transformation and high-quality development.