The PAD (Property Address Directory) file contains additional geographic information at the tax lot level not found in the PLUTO files. This data includes alias addresses and Building Identification Numbers (BINs). It consists of two ASCII, comma delimited files: a tax lot file and an address file. All previously released versions of this data are available at BYTES of the BIG APPLE- Archive.
BatchData provides comprehensive home ownership data for 87 million owners of residential homes in the US. We specialize in providing accurate contact information for owners of specific properties, trusted by some of the largest real estate companies for our superior capabilities in accurately unmasking owners of properties that may be hidden behind LLCs and corporate veils.
Our home ownership data is commonly used to fuel targeted marketing campaigns, generating real estate insights, powering websites/applications with real estate intelligence, and enriching sales and marketing databases with accurate homeowner contact information and surrounding intelligence to improve segmentation and targeting.
Home ownership data that is linked to a given property includes: - Homeowner Name(s) - Homeowner Cell Phone Number - Homeowner Email Address - Homeowner Mailing Address - Addresses of Properties Owned - Homeowner Portfolio Equity - Total Number of Properties Owned - Property Characteristics of Properties Owned - Homeowner sales, loan, and mortgage information - Property Occupancy Status of Properties Owned - Property Valuation & ARV information of Properties Owned - Ownership Length - Ownership History - Homeowner Age - Homeowner Marital Status - Homeowner Income - and more!
BatchService is both a data and technology company helping companies in and around the real estate ecosystem achieve faster growth. BatchService specializes in providing accurate B2B and B2C contact data for US property owners, including in-depth intelligence and actionable insights related to their property. Our portfolio of products, services, and go-to-market expertise help companies identify their target market, reach the right prospects, enrich their data, consolidate their data providers, and power their products and services.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset contains property sales data, including information such as PropertyID, property type (e.g., Commercial or Residential), tax keys, property addresses, architectural styles, exterior wall materials, number of stories, year built, room counts, finished square footage, units (e.g., apartments), bedroom and bathroom counts, lot sizes, sale dates, and sale prices. Explore this dataset to gain insights into real estate trends and property characteristics.
Field Name | Description | Type |
---|---|---|
PropertyID | A unique identifier for each property. | text |
PropType | The type of property (e.g., Commercial or Residential). | text |
taxkey | The tax key associated with the property. | text |
Address | The address of the property. | text |
CondoProject | Information about whether the property is part of a condominium | text |
project (NaN indicates missing data). | ||
District | The district number for the property. | text |
nbhd | The neighborhood number for the property. | text |
Style | The architectural style of the property. | text |
Extwall | The type of exterior wall material used. | text |
Stories | The number of stories in the building. | text |
Year_Built | The year the property was built. | text |
Rooms | The number of rooms in the property. | text |
FinishedSqft | The total square footage of finished space in the property. | text |
Units | The number of units in the property | text |
(e.g., apartments in a multifamily building). | ||
Bdrms | The number of bedrooms in the property. | text |
Fbath | The number of full bathrooms in the property. | text |
Hbath | The number of half bathrooms in the property. | text |
Lotsize | The size of the lot associated with the property. | text |
Sale_date | The date when the property was sold. | text |
Sale_price | The sale price of the property. | text |
Data.milwaukee.gov, (2023). Property Sales Data. [online] Available at: https://data.milwaukee.gov [Accessed 9th October 2023].
Open Definition. (n.d.). Creative Commons Attribution 4.0 International Public License (CC BY 4.0). [online] Available at: http://www.opendefinition.org/licenses/cc-by [Accessed 9th October 2023].
BatchData provides new homeowner data including property owner(s) email, phone number and mailing address. Demographic data, mortgage data, and other related property information can also be included and delivered in bulk on a scheduled basis, or on demand via API.
This table contains the legal description information including legal address (site address), deeded land area, and tax district for properties within Fairfax County. There is a one to one relationship to the parcels data. Refer to this document for descriptions of the data in the table.
BatchData is used by lead generation, product, operations, and acquisitions teams to power websites, fuel applications, build lists, enrich data, and improve data governance. A suite of APIs and self-service list building platforms provide access to 150M+ residential properties.
Residential Real Estate Data includes: - Property Address Information - Assessment Details - Building Characteristics - Demographics - Foreclosure - Occupancy/Vacancy - Involuntary Liens - MLS & Agent Arrays - Owner Names & Mailing Address - Property Owner Profiles - Current & Prior Sales - Tax Information - Valuation & Equity
Real Estate Data APIs include: - Residential Property Search - Residential Property Lookup - Residential Address Verification - Residential Property Skip Trace - Geocoding
BatchData's robust data science team curates over a dozen primary and secondary tier 1 data sources to offer unparalleled database depth, accuracy, and completeness.
https://www.fairfaxcounty.gov/maps/disclaimerhttps://www.fairfaxcounty.gov/maps/disclaimer
This data includes the owner name and address for properties within Fairfax County. There is a one to one relationship to the parcel data.The layer contains the parcel owner's full name and address for all parcels within Fairfax County, VA. If an owner has requested that their name not be shown then the owner name has been hidden. This data is created by joining the DTA (Department of Tax Administration) owner data table to the GIS parcels polygons. The source DTA owner table is updated every night. Contact: Fairfax County GIS DivisionData Accessibility: PublicUpdate frequency: DailyCreation date: 5/5/2020Layer Name: GISMGR.PARCEL_GIS_OWNDATADDR
This data contains active Real Estate Salesperson and Broker Licenses from New York State Department of State (DOS). Each line will be either an individual or business licensee which holds business address and license number information. If the license type is an individual, the business name that the individual works for will be listed.
Our extensive database contains approximately 800,000 active rental property listings from across the United States. Updated daily, this comprehensive collection provides real estate professionals, investors, and property managers with valuable market intelligence and business opportunities. Database Contents
Property Addresses: Complete location data including street address, city, state, ZIP code Listing Dates: Original listing date and most recent update date Availability Status: Currently available, pending, or recently rented properties Geographic Coverage: Properties spanning all 50 states and major metropolitan areas
Applications & Uses
Market Analysis: Track rental pricing trends across different regions and property types Investment Research: Identify high-opportunity markets with favorable rental conditions Lead Generation: Connect with property owners potentially needing management services Competitive Intelligence: Monitor listing volumes, vacancy rates, and market saturation Business Development: Target specific neighborhoods or property categories for expansion
File Format & Delivery
Organized in easy-to-use CSV format for seamless integration with data analysis tools Accessible through secure download portal or API connection Daily updates ensure you're working with the most current market information Custom filtering options available to narrow results by location, date range, or other criteria
Data Quality
Rigorous validation processes to ensure address accuracy Duplicate listing detection and removal Regular verification of active status Standardized format for consistent analysis
Subscription Benefits
Access to historical listing archives for trend analysis Advanced search capabilities to target specific property characteristics Regular market reports summarizing key trends and opportunities Custom data exports tailored to your specific business needs
AK ~ 1,342 listings AL ~ 6,636 listings AR ~ 4,024 listings AZ ~ 25,782 listings CA ~ 102,833 listings CO ~ 14,333 listings CT ~ 10,515 listings DC ~ 1,988 listings DE ~ 1,528 listings FL ~ 152,258 listings GA ~ 28,248 listings HI ~ 3,447 listings IA ~ 4,557 listings ID ~ 3,426 listings IL ~ 42,642 listings IN ~ 8,634 listings KS ~ 3,263 listings KY ~ 5,166 listings LA ~ 11,522 listings MA ~ 53,624 listings MD ~ 12,124 listings ME ~ 1,754 listings MI ~ 12,040 listings MN ~ 7,242 listings MO ~ 10,766 listings MS ~ 2,633 listings MT ~ 1,953 listings NC ~ 22,708 listings ND ~ 1,268 listings NE ~ 1,847 listings NH ~ 2,672 listings NJ ~ 31,286 listings NM ~ 2,084 listings NV ~ 13,111 listings NY ~ 94,790 listings OH ~ 15,843 listings OK ~ 5,676 listings OR ~ 8,086 listings PA ~ 37,701 listings RI ~ 4,345 listings SC ~ 8,018 listings SD ~ 1,018 listings TN ~ 15,983 listings TX ~ 132,620 listings UT ~ 3,798 listings VA ~ 14,087 listings VT ~ 946 listings WA ~ 15,039 listings WI ~ 7,393 listings WV ~ 1,681 listings WY ~ 730 listings
Grand Total ~ 977,010 listings
Zillow Properties Listing dataset to access detailed real estate listings, including property prices, locations, and features. Popular use cases include market analysis, property valuation, and investment decision-making in the real estate sector.
Use our Zillow Properties Listing Information dataset to access detailed real estate listings, including property features, pricing trends, and location insights. This dataset is perfect for real estate agents, investors, market analysts, and property developers looking to analyze housing markets, identify investment opportunities, and assess property values.
Leverage this dataset to track pricing patterns, compare property features, and forecast market trends across different regions. Whether you're evaluating investment prospects or optimizing property listings, the Zillow Properties dataset offers essential information for making data-driven real estate decisions.
This is a collection of CSV files that contain assessment data. The files in this extract are:
Primary Parcel file containing primary owner and land information;Addn file containing drawing vectors for dwelling records;Additional Address file containing any additional addresses that exist for a parcel;Assessment file containing assessed value-related data;Appraisal file containing appraised value-related data;Commercial file containing primary commercial data;Commercial Apt containing commercial apartment data;Commercial Interior Exterior dataDwelling fileEntrance data containing data from appraisers' visits;Other Buildings and Yard ImprovementsSales FileTax Rate File for the current billing cycle by taxing district authority and property class; and,Tax Payments File containing tax charges and payments for current billing cycle.
Explore Doorda's UK Geospatial Real Estate Data, offering insights into 34M+ Addresses aggregated from 10 data sources. Unlock Customer Insights and Enhanced Location Planning Capabilities.
This is a collection of CSV files that contain assessment data. The files in this extract are:
Primary Parcel file containing primary owner and land information;Addn file containing drawing vectors for dwelling records;Additional Address file containing any additional addresses that exist for a parcel;Assessment file containing assessed value-related data;Appraisal file containing appraised value-related data;Commercial file containing primary commercial data;Commercial Apt containing commercial apartment data;Commercial Interior Exterior dataDwelling fileEntrance data containing data from appraisers' visits;Other Buildings and Yard ImprovementsSales FileTax Rate File for the current billing cycle by taxing district authority and property class; and,Tax Payments File containing tax charges and payments for current billing cycle.In addition to the CSV files, the following are included:
Data Dictionary PDF; and,St Louis County Rate Book for the current tax billing cycle.
We used the open-access Zillow Inc. GetSearchResults API to sample house data for each ZPID in accordance with daily API call limits. For more information on the API see the official documentation page: https://www.zillow.com/howto/api/GetSearchResults.htm. We anonymized the property address and ZPID fields.
This data represents all of the County’s residential real estate properties and all of the associated tax charges and credits with that property processed at the annual billing in July of each year, excluding any subsequent billing additions and/or revisions throughout the year. This dataset excludes the names of the property owners. The addresses in this database represent the address of the property. For more information about the individual taxes and credits, please go to http://www.montgomerycountymd.gov/finance/taxes/faqs.html#credit. Update Frequency: Updated Annually in July
This dataset represents real estate assessment and sales data that is updated on a quarterly basis by the Real Estate Assessor’s Office. This dataset contains information for properties in the city including: Acreage, Square footage, GPIN, Street Address, year built, current land value, current improvement values, and current total value. The information is obtained from Real Estate Assessor’s Office ProVal records database.
For data about this dataset, please click on the below link: https://data.norfolk.gov/Real-Estate/Property-Assessment-and-Sales-FY19/th3n-jr9u/about_data
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This data set represents real estate market announcements monitoring data in Latvia in 2023. The data was collected from online ads site ss.com. The database contains 209,9 thousand ads and consists of 24 groups of data (type of deal, price, characteristics and address of real estate, etc.). The data reflects the dynamics of price changes by months (at the beginning of the month) in 2023. Monitoring continued in 2023 was started in 2018. In 2023 the new impuls of data application was found. It is associated with the possibility of planning the urban environment taking into account the transition of transport to environment friendly fuel types.
This dataset represents real estate assessment and sales data made available by the Office of the Real Estate Assessor. This dataset contains information for properties in the city, including acreage, square footage, GPIN, street address, year built, current land value, current improvement value, and current total value. The information is obtained from the Office of the Real Estate Assessor ProVal records database. This dataset is updated daily.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Update Frequency: Daily
A record for each address in the city. It contains addresse(s) including a mailable field for the purpose of creating mailing lists. The file is available in three formats for the current month.
To download XML and JSON files, click the CSV option below and click the down arrow next to the Download button in the upper right on its page.
Explore Doorda's UK Residential Real Estate Data, offering insights into 34M+ Addresses sourced from 20 data sources. Unlock business intelligence and analytics capabilities.
The PAD (Property Address Directory) file contains additional geographic information at the tax lot level not found in the PLUTO files. This data includes alias addresses and Building Identification Numbers (BINs). It consists of two ASCII, comma delimited files: a tax lot file and an address file. All previously released versions of this data are available at BYTES of the BIG APPLE- Archive.