A big data technique-based supply chain management decision support system comprises: an information acquisition module; an analysis processing module; a visualization module; and a support module. The information acquisition module is used to extract data from a big data source, convert a format of the data, and send the same to the analysis processing module. The analysis processing module is used to search for useful information in the data sent by the information acquisition module, and perform integration and analysis on the found information to provide an analysis result. The visualization module is used to display the analysis result. The support module comprises a database, a textile classification database and an access control submodule. The supply chain management decision support system can identify an extreme emotion of a user, notify, on the basis of a client emotion report, the user of a corresponding action to be taken, and search for a cost-effective solution, thereby increasing cost utilization efficiency.
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