Address Spine – UK address level property information SAMPLE DATA

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: - PAF UDPRN for UK postal areas of Bristol (BS) and Halifax (HX) with address variables appended containing XXXXX records Fields Included: Category Variable Name Variable Label Address udprn_key Unique Delivery Point Reference Number Address address_line_1 Address line 1 Address address_line_2 Address line 2 Address address_line_3 Address line 3 Address address_line_4 Address line 4 Address address_line_5 Address line 5 Address address_line_6 Address line 6 Address address_line_7 Address line 7 Address address_line_8 Address line 8 Address postcode postcode Geolocation lat Latitude Geolocation long Longitude Geolocation northing Northing Geolocation easting Easting Geographical admin codes lsoa11 lsoa11 Geographical admin codes msoa11 msoa11 Geographical admin codes region11 region11 Geographical admin codes ualad11 ualad11 Geographical admin codes ctyua11 ctyua11 Geographical admin codes gor region code Home mr_flag Multi residency flag Home number_of_households PAF household count Home residential_flag Residential flag Home dr_tenure Housing tenure Dwelling dwelling_footprint_msq Total dwelling footprint in square metres Dwelling dwelling_npafhhs No of PAF households per dwelling Dwelling dw_m2_per_pafhhs Dwelling footprint per household in square metres Property epc_inspection_date EPC inspection date Property dr_hageband_hybrid Property age band (For E&W only) Property source_hageband_hybrid_b Flag to indicate origin of property age Property epc_dr_extention_cnt No of extensions Property epc_dr_habitable_rooms_cnt No of habitable rooms Property dr_htype_hybrid Property type Property source_htype_hybrid_b Flag to indicate origin of house type Property epc_dr_rooftype Roof type Property epc_dr_wallstype Wall type Property epc_dr_glazedtype Glazing type Property - Price lr_dr_soldprice Last sold price Property - Price lr_date Date last sold Property - Price lr_dr_currentprice Current estimated price Property - Price dr_curprice_persq_epc Estimated price per square metre Property - Floors epc_dr_floor_level Floor level Property - Floors epc_dr_topfloor_flag Top floor flag Property - Floors epc_dr_midfloor_flag Mid floor flag Property - Floors dr_storey_cnt_hybrid Flat story count Property - Floors source_storey_hybrid_b Flag to indicate origin of flat storey count Property - Floors epc_dr_floor_area Total Floor areas in square metres Property - Environment epc_dr_env_impact Environmental impact Property - Environment epc_dr_wind_turbine_cnt Wind turbine count Property - Environment epc_dr_solar_water_heating_flag Solar water heating Property - Environment epc_dr_current_eng_rating Current energy rating/efficiency Property - Environment epc_dr_potential_eng_rating Potential energy rating/efficiency Property - Energy epc_dr_mainheat_boilerrad Main heat radiator Property - Energy epc_dr_mainheat_eff Mainheat energy efficiency Property - Energy epc_dr_main_gas_flag Mains gas Property - Energy epc_dr_energy_tariff Energy tariff Property - Energy epc_dr_eng_comsup_curr Energy consumption current Property - Energy epc_dr_eng_comsup_poten Energy consumption potential Postcode - Broadband speed ofcom_dr_ultrafast 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

该数据集是英国地址级房产信息的样本，整合了超过2900万住宅地址的多种属性，包括房产类型、价格、能耗及地理编码等变量。它通过地理空间建模技术补充数据，并支持通过UDPRN或地理标识进行查询，可用于匹配客户数据以支持房产相关决策分析。