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.