Construction of Multidimensional Analysis Model of Power Data and Financial Data Fusion

By integrating the accuracy and real-time of power data and the comprehensiveness and complexity of financial data, this model can provide more accurate risk assessment basis for financial institutions, broaden financing channels for small and medium-sized enterprises, and promote the sustainable development of power industry. In this paper, the power data indicators such as power consumption volatility and timely rate of electricity payment, as well as financial data indicators such as current ratio and asset-liability ratio are selected, and the weight of each indicator is determined by CRITIC weight method to ensure the rationality and effectiveness of the weight. The model adopts star structure, including core fact table and multiple dimension tables, which supports time series analysis, and combines the index calculation layer and data visualization interface to visually display the analysis results. Taking X Company, a small and medium-sized manufacturing enterprise, as a case, this paper comprehensively analyzes its power consumption behavior and financial performance through the model, accurately evaluates the credit status and risk level of the enterprise, and proves the effectiveness and practicability of the model. The findings indicate that the multi-dimensional analysis model offers robust support for credit decisions made by financial institutions, facilitating a deeper integration between the physical economy and the digital sector. This, in turn, contributes to the advancement of socioeconomic development with higher quality.