Multi-Level and Multi-Dimensional Assessment for High-Value Data Elements

Digitalization has deeply integrated into various industries, promoting comprehensive upgrades from automation to informatization. As a crucial asset, data has become essential to enhancing productivity, making the efficient utilization of structured data assets imperative. Although many researchers have investigated structured data asset evaluation, there is still a lack of a comprehensive data element value assessment model, particularly one that evaluates structured data across multiple layers and dimensions. Therefore, we conduct research and analysis on data asset evaluation models and construct a value assessment method that involves database, table, row, and column-level metrics. Through systematic analysis of data importance, this method can comprehensively and accurately identify high-value data elements within structured data assets, maximizing their value and providing a solid foundation for enterprises' digital transformation.