This invention relates to a
data analysis-based
enterprise data management method, comprising the following steps: collecting multi-dimensional data from both internal and external sources of the enterprise and preprocessing the data; extracting three core features from the preprocessed effective data; constructing a
data value-risk linkage assessment model based on the core features, calculating the comprehensive value
score and
risk level of the enterprise data; sorting the data in descending order based on the comprehensive value
score, outputting high-value data for enterprise decision support, and triggering corresponding early warning mechanisms according to the
risk level; and dynamically updating the parameters of the
data value-risk linkage assessment model based on feedback data from enterprise users regarding the effectiveness of
data application, achieving
adaptive optimization of the model. In this invention, by integrating three types of features—business relevance, value density, and risk warning—and introducing a time
decay factor, a multi-dimensional
value assessment model can be constructed to accurately identify high-value data.