Application of Data Mining Technology in Urban Economic Statistical Data Analysis

Under the background of economic globalization and informatization, the complexity and uncertainty of urban economic development situation are increasing day by day. Urban economic statistical data has also become an important carrier to reflect the operation of urban economy, and its accuracy and timeliness are directly related to the scientific and effective economic decision-making. However, the traditional data analysis and processing methods often follow the old logical framework, which shows obvious limitations in the face of massive, multidimensional and multi-source urban economic statistical data, and it is difficult to fully display the value behind urban economic statistics. In this regard, based on the actual application requirements, this paper will deeply analyze the application feasibility of data mining technology in urban economic statistical data analysis, and verify the application effect of data mining technology through actual case tests. Practice has proved that by K-means cluster analysis, urban economy can be divided into different regions or types, which reveals the economic characteristics and advantages of each region, and can significantly improve the efficiency and quality of urban economic statistical data analysis, thus providing more powerful technical support for urban economic development.