Address Spine – UK address level property information

CACI’s Address Spine is made up of key property level variables linked to an address or UDPRN that come from a range of sources, combined and deduplicated by CACI’s team of data scientists to create a single core residential property file. The file of over 29m residential addresses includes variables such as property type, number of rooms, tenure, estimated current house price, energy consumption, geo-location and many more. In addition to the ‘real’ data, CACI have imputed variables such as the type of property or current house price value using geospatial modelling techniques combined with known data on the same street or in the same postcode to increase the volume of data available. The variables can be coded against your address data using a UDPRN or can be queried based on geographical identifiers. Tables Included: - Current UK PAF UDPRN with variables appended Fields Included: CACI’s Address Spine is made up of key property level variables linked to an address or UDPRN that come from a range of sources, combined and deduplicated by CACI’s team of data scientists to create a single core residential property file. The file of over 29m residential addresses includes variables such as property type, number of rooms, tenure, estimated current house price, energy consumption, geo-location and many more. In addition to the ‘real’ data, CACI have imputed variables such as the type of property or current house price value using geospatial modelling techniques combined with known data on the same street or in the same postcode to increase the volume of data available. The variables can be coded against your address data using a UDPRN or can be queried based on geographical identifiers. Tables Included: - Current UK PAF UDPRN with variables appended Fields Included: Category Variable Label Address Unique Delivery Point Reference Number Address Address line 1 Address Address line 2 Address Address line 3 Address Address line 4 Address Address line 5 Address Address line 6 Address Address line 7 Address Address line 8 Address postcode Geolocation Latitude Geolocation Longitude Geolocation Northing Geolocation Easting Geographical admin codes lsoa11 Geographical admin codes msoa11 Geographical admin codes region11 Geographical admin codes ualad11 Geographical admin codes ctyua11 Geographical admin codes region code Home Multi residency flag Home PAF household count Home Residential flag Home Housing tenure Dwelling Total dwelling footprint in square metres Dwelling No of PAF households per dwelling Dwelling Dwelling footprint per household in square metres Property EPC inspection date Property Property age band (For E&W only) Property Flag to indicate origin of property age Property No of extensions Property No of habitable rooms Property Property type Property Flag to indicate origin of house type Property Roof type Property Wall type Property Glazing type Property - Price Last sold price Property - Price Date last sold Property - Price Current estimated price Property - Price Estimated price per square metre Property - Floors Floor level Property - Floors Top floor flag Property - Floors Mid floor flag Property - Floors Flat story count Property - Floors Flag to indicate origin of flat storey count Property - Floors Total Floor areas in square metres Property - Environment Environmental impact Property - Environment Wind turbine count Property - Environment Solar water heating Property - Environment Current energy rating/efficiency Property - Environment Potential energy rating/efficiency Property - Energy Main heat radiator Property - Energy Mainheat energy efficiiency Property - Energy Mains gas Property - Energy Energy tariff Property - Energy Energy consumption current Property - Energy Energy consumption potential Postcode - Broadband speed Ultrafast Example Use Case: 1) Join the property attributes to your customer data using UDPRN to inform decisions on the type of products your customers may be interested in eg promote first time buyer mortgages to those in privately rented accommodation. 2) Understand information about a particular region such as average house price.

搜集汇总

背景与挑战

背景概述

CACI的Address Spine是一个整合多源数据的英国住宅房产核心文件，涵盖超过2900万个地址的房产类型、房间数、产权、房价估计和能耗等变量，并利用地理空间建模技术补充估算数据。该数据集支持通过UDPRN或地理标识进行查询，适用于客户数据分析或区域洞察等应用场景。