中国房地产大数据平台
收藏资源简介：
房谱科技房地产大数据平台对海量多源异构房地产数据自动采集获取、多模态融合清洗和异构数据集成，以深度挖掘为核心进行大数据多维智能分析，实现了批处理-流处理相结合的大数据管理。建立了中国城市“地、楼、栋、户”一体的数据底座（楼盘字典），超过15年数据积累房源总量近1亿套且精准到户，数据覆盖量占国内1/3，涵盖土地13.4万宗、楼盘9.87万条、楼栋210万条、房源信息10203条，具备房地产行业覆盖范围广泛，颗粒度细致的高质量基础数据。房地产大数据平台数据产品形态为非界面化产品，可通过API或数据集方式提供服务。数据产品具备完整的房地产大数据体系与完善的各类基础数据库和相关专题库，输出统一数据标准，实现数据资源清单化管理。主要应用于智慧城市房地产数据底座建设、数字房产一体化建设、房地产政务/公共服务系统开发等场景，为用户提供详细的土地、楼盘、楼栋、户及房地产市场分析与决策等数据。
Fangpu Technology's Real Estate Big Data Platform automatically collects massive multi-source heterogeneous real estate data, performs multimodal fusion cleaning and heterogeneous data integration, conducts multi-dimensional intelligent big data analysis with deep mining as the core, and realizes big data management integrating batch processing and stream processing. It has built a unified data infrastructure (real estate property dictionary) covering land parcels, real estate developments, individual buildings and housing units for Chinese cities. With over 15 years of data accumulation, the total number of housing units reaches nearly 100 million with precise granularity down to individual housing units, and its data coverage accounts for one-third of the domestic real estate market. The platform covers 134,000 land parcels, 98,700 real estate development entries, 2.1 million building entries and 10,203 housing unit information entries, and boasts high-quality basic data with wide coverage across the real estate industry and fine granularity. The data products of this platform are non-interface-based, and can be provided via APIs or dataset distribution modes. The data products feature a complete real estate big data system, comprehensive basic databases and related thematic databases, adopt unified data standards, and realize inventory management of data resources. It is mainly applied in scenarios such as the construction of real estate data infrastructures for smart cities, integrated digital real estate construction, and the development of real estate government affairs/public service systems, providing users with detailed data including land, real estate developments, individual buildings, housing units and real estate market analysis and decision-making support data.
