山西省经济财政债务数据

本数据产品依托明树基建投融资大数据库和自主研发的低代码平台，利用政府公开网站如山西省人民政府、财政厅、统计局等公布的财政决算报告、财政预算执行报告、财政预算报告、统计公报、统计年鉴等公开披露文件进行合法合规的人工采集，已投入团队20人，耗费3年的时间使用自主研发的系统和数据中台进行数据清洗、处理、分析和加工形成结构化数据，人工采集重点字段如：财政预算收支、政府性基金收支、国营资本收支、社会保险收支、政府债务余额、政府债务限额等字段，并逐期进行动态更新，在保证数据隐私安全及合法合规的基础上，运用灵活多变的模型算法构建数据场景，搭建区域经济指标浏览器、区域对比工具、区域GDP榜单、区域债务预警等模块专题，通过自定义数据指标模板实现灵活配置指标组合、不同维度的数据抓取及数据碰撞检验，生成完整真实公正的数据集、数据报告等结果。

This data product is developed based on the Mingshu Infrastructure Investment and Financing Large Database and an independently developed low-code platform. It conducts legally and compliantly manual data collection using publicly disclosed documents such as financial final accounts reports, financial budget implementation reports, financial budget reports, statistical communiqués and statistical yearbooks released by official government websites including the People's Government of Shanxi Province, the Department of Finance and the Bureau of Statistics. A team of 20 members has been deployed for the project, and over a period of 3 years, structured data has been generated through data cleaning, processing, analysis and enrichment using independently developed systems and data middle platforms. Key manually collected fields include fiscal budget revenues and expenditures, government fund revenues and expenditures, state-owned capital revenues and expenditures, social insurance revenues and expenditures, government debt balance, government debt limit and other relevant fields, with dynamic updates carried out on a periodic basis. While ensuring data privacy, security and compliance, flexible and adaptable model algorithms are used to construct data scenarios, and specialized modules such as the regional economic indicator browser, regional comparison tool, regional GDP rankings and regional debt early warning system are built. Through customizable data indicator templates, flexible configuration of indicator combinations, data crawling across different dimensions and data collision verification are realized, generating complete, authentic and fair datasets, data reports and other outcomes.