全国基建项目中标数据

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全国公共资源交易平台成交公示信息等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：项目名称、预算金额、采购需求、供应商名称、中标金额、采购人信息、采购代理机构信息、项目概况、建设期、合作期、项目地区、企业工商信息等字段，并对全国各个重点模式如PPP、EPC、施工总承包、EPC+F、设计施工总承包、EPC+O、股权投资+施工总承包、EPC+F+O、ABO、勘察设计、其他类型、其他投资类、特许经营、委托运营、服务采购等模式的项目进行招投标追踪，每日进行动态更新，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，可根据项目拓展、竞争对手分析、项目运营等不同场景，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 Big Database and a self-developed low-code platform. It legally and compliantly collects data manually from official government websites, including transaction announcement information from the National Public Resource Trading Platform and other similar platforms. A team of 20 members has dedicated 3 years to data cleaning, processing, analysis and curation using self-developed systems and a data middle platform to generate structured data. Key fields manually collected include project name, budget amount, procurement requirements, supplier name, winning bid amount, procurer information, procurement agency information, project overview, construction period, cooperation period, project location, enterprise industrial and commercial information and other core fields. The product also conducts bidding tracking for projects under various key domestic delivery and investment models, including PPP (Public-Private Partnership), EPC (Engineering, Procurement and Construction), general construction contracting, EPC+Financing (EPC+F), design-construction general contracting, EPC+Operation (EPC+O), equity investment + general construction contracting, EPC+Financing+Operation (EPC+F+O), ABO (Authority-Built-Operate), survey and design, other types, other investment categories, concession operation, entrusted operation, service procurement and other models. The data is updated dynamically on a daily basis. On the premise of ensuring data privacy, security and compliance, flexible and diverse model algorithms are used to build data scenarios. For different application scenarios such as project expansion, competitor analysis and project operation, users can flexibly configure indicator combinations, perform data extraction across different dimensions and conduct data collision verification through custom data indicator templates, and generate complete, authentic and fair datasets, data reports and other outcomes.

搜集汇总

背景与挑战

背景概述

该数据集基于政府公开信息，经人工采集和系统处理形成结构化数据，涵盖全国基建项目的中标信息、采购详情及企业数据，支持多种项目模式追踪和动态更新，适用于各类商业分析场景。