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Develops a visual system to optimize enterprise expense data analysis, indicating improved decision-making capabilities.
This study focuses on the visualization design and implementation of enterprise expense data, based on the theory of the whole value chain, aiming to address the issues of data redundancy and analytical difficulties in modern enterprise management information systems. The research constructs a system that integrates and visualizes expense data from various systems. Through intuitive and comprehensive analytical tools, the system supports managers in transcending system boundaries to achieve rapid and accurate decision-making from a global data perspective. Built upon the theory of the whole value chain, this system covers core activities such as raw material procurement, production and processing, and product sales, as well as supporting activities including finance and human resources. Adopting a front-end and back-end separation architecture with technologies such as React.js and Node.js, the system ensures flexibility, maintainability, and scalability. Furthermore, it designs associated data table structures and optimizes indexes to enhance query efficiency. By presenting data through visualization, the system provides managers with intuitive and comprehensive analytical tools to optimize resource allocation and improve enterprise competitiveness.
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Wu Shuang (2026) studied this question.
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