In 2023 and the first half of 2024, the largest property sale in the data center real estate market in Europe was DATA4 Paris-Saclay in Paris. In April 2023, Brookfield bought the 47,300 square meter property from AXA for an undisclosed price. The most expensive sale was Digital Frankfurt I. The valuation of the site was 270 million U.S. dollars and Digital Core REIT obtained 24.9 percent from Digital Realty.

What Makes Our Data Unique? We do not buy and resell other provider's data. We aggregate our housing data, which we source ourselves, to ensure the highest quality.

Our real estate data encompasses a wide range of comprehensive information on homeowners and properties.

• Current listings as well as properties for rent.
• Current and past property owners
• Current and past building permits
• Property attributes such as number of rooms, square footage, roof type, and many more.
• Zoning details
• Businesses at location
• Forclosure details
• Current and historical property values
• Tax details

Use cases and verticals.

• Developers looking to create applications around real estate data tailored towards real estate investors or agents.
• Agents or investors looking to acquire new leads within a geographical territory.
• Market analysts looking to uncover trends within the housing sector.

Our Property Owner Data provides a wealth of information that can be key to your marketing strategy. Containing over 128 Million residential properties covering 99% of all properties from more than 3,000 counties nationwide with as many as 200 property data attributes per record. Each Property Data record is acquired from the Assessor’s Parcel Number and is verified before being added into the database.

STATS:
-128 Million Residential Property Data Records
-93 Million Emails
-72 Million Phones - Over 90% Mobile Ad ID and Hashed Email Coverage

Boost your property marketing efforts with our extensive Property Owner Data. Ideal for direct mail, email, and digital campaigns, our data provides the insights you need to target effectively and drive results.

In a market brimming with opportunities, standing out requires a deep understanding of property insight and buyer behaviors. Our Property Owner Data offers detailed information on property attributes, ownership history, and detailed mortgage insight. Whether you're focusing on home services, lending or real estate investing, our property data helps you craft targeted campaigns that hit the mark.

Access comprehensive Property Owner Data such as property type, valuation, and recent sales data. This allows you to segment your audience and tailor your messaging to address their specific needs. With targeted email campaigns, direct mail and online ads, you can reach your ideal prospects and convert them into loyal clients.

Enhance your marketing strategy, increase engagement, and close more deals by leveraging our robust Property Owner Data. Empower your campaigns with insights that drive growth and success in the competitive real estate landscape.

Contact one of our team members today for a free test.

This dataset is created by the Town of Cary GIS Group. It contains data from the western portion of Wake County, the eastern portion of Chatham County, and the southern portion of Durham County. It has been modified from the original sources to act as one layer for use by the Town of Cary. This file is updated once a month from the respective sources. Please refer to each Counties' data for the latest information:

Wake County

Durham County

Chatham County

Graph and download economic data for Median Sales Price of Houses Sold for the United States (MSPUS) from Q1 1963 to Q4 2024 about sales, median, housing, and USA.

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.

Real estate is a dynamic and ever-evolving industry that relies heavily on data to make informed decisions. One of the fundamental aspects of this industry is real estate listing data. This data encompasses detailed information about properties that are available for sale or rent in a given market. It plays a pivotal role in assisting buyers, sellers, real estate professionals, and investors in making well-informed choices. In this data brief, we will provide an overview of what real estate listing data is and highlight five key industry use cases.

Real Estate Listings Data Includes:

• Property Location
• 50+ Property and Building Characteristics
• School District Information
• List Date
• Listing Price - Maximum, Minimum, Sold Price
• Listing Status
• Number of Days on Market
• Listing Agent and Office

China PMI: Real Estate: Inventory data was reported at 30.100 % in Dec 2009. This records an increase from the previous number of 29.800 % for Nov 2009. China PMI: Real Estate: Inventory data is updated monthly, averaging 38.400 % from Jan 2008 (Median) to Dec 2009, with 24 observations. The data reached an all-time high of 49.200 % in May 2008 and a record low of 29.800 % in Nov 2009. China PMI: Real Estate: Inventory data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Business and Economic Survey – Table CN.OP: Purchasing Managers' Index: Non Manufacturing: Real Estate.

This dataset contains data on all Real Property parcels that have sold since 2013 in Allegheny County, PA.

Before doing any market analysis on property sales, check the sales validation codes. Many property "sales" are not considered a valid representation of the true market value of the property. For example, when multiple lots are together on one deed with one price they are generally coded as invalid ("H") because the sale price for each parcel ID number indicates the total price paid for a group of parcels, not just for one parcel. See the Sales Validation Codes Dictionary for a complete explanation of valid and invalid sale codes.

Sales Transactions Disclaimer: Sales information is provided from the Allegheny County Department of Administrative Services, Real Estate Division. Content and validation codes are subject to change. Please review the Data Dictionary for details on included fields before each use. Property owners are not required by law to record a deed at the time of sale. Consequently the assessment system may not contain a complete sales history for every property and every sale. You may do a deed search at http://www.alleghenycounty.us/re/index.aspx directly for the most updated information. Note: Ordinance 3478-07 prohibits public access to search assessment records by owner name. It was signed by the Chief Executive in 2007.

Yearly Real Estate sales data by count and purchase price (median and average) from 2005 to 2018. All communities in the Keys to the Valley region are included.

Vermont Dataset Description

Purchase price - Average Sales Price based on listing price at time of purchase

Source – www.HousingData.org

NH Dataset Description

This data set provides an estimate of the median sale price of existing and new primary homes in New Hampshire. A primary home is defined as a single family home occupied by an owner household as their primary place of residence. Multi-family rental housing, seasonal or vacation homes and manufactured housing are not included in the analysis of this data.

Purchase price -
Median Sales Price

Data Collection Process - For the Period 1990 through 2014, the median purchase prices were calculated from data collected by the New Hampshire Department of Revenue Administration on the PA-34 Form through their vendor Real Data Corp. A PA-34 Form is filed by the buyer and seller at the time of sale of all real property in the State of New Hampshire. In 2015 this source of data was no longer available, and has been replaced by real estate transaction data supplied by The Warren Group and filtered and compiled by NHHFA. This change in data source is reflected in the charts by a break in the trend line.

Analysis - Median sale prices of all, new, existing, and condominium homes are calculated. The frequency of sales by $10,000 increment is also calculated for each of the above categories. Calculations based on sample sizes smaller than 50 are viewed as providing inconsistent and highly volatile results and are not typically released. Individual record level data is not released.

Limitations - The quality of this data at the higher geographic levels (statewide and counties) is consistent over the entire time series. For the larger LMAs and Municipalities the data is reasonably consistent with some holes in the data. For smaller LMAs and moderate sized municipalities the data is most consistent for existing homes since 1998. For the smallest municipalities this data set does not provide adequately consistent analysis.

Source - NHHFA Purchase Price Database; Source: 1990-2014 - NH Dept. of Revenue, PA-34 Dataset, Compiled by Real Data Corp. Filtered and analyzed by New Hampshire Housing.

https://www.nhhfa.org/publications-data/housing-and-demographic-data/

This table contains property sales information including sale date, price, and amounts for properties within Fairfax County. There is a one to many relationship to the parcel data. Refer to this document for descriptions of the data in the table.

Key information about House Prices Growth

• US house prices grew 5.2% YoY in Sep 2024, following an increase of 6.2% YoY in the previous quarter.
• YoY growth data is updated quarterly, available from Mar 1992 to Sep 2024, with an average growth rate of 5.5%.
• House price data reached an all-time high of 17.7% in Sep 2021 and a record low of -12.4% in Dec 2008.

Gain an in-depth view of property characteristics for more than 157 million properties across the United States (also available at the state- and county-level).

This dataset mainly provides the actual information of real estate transactions declared by the declared person nationwide (providing MANIFEST.CSV, schema-main.csv, schema-build.csv, schema-land.csv, schema-park)Released once on the 1st, 11th, and 21st of each month

Graph and download economic data for Housing Inventory: Median Days on Market in the United States (MEDDAYONMARUS) from Jul 2016 to Feb 2025 about median and USA.

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.

Brazil Loans: Real Estate Financing: Value: for Purchase: Residential Building: Market Rate: Southeast: Rio de Janeiro data was reported at 28,589,033.000 BRL in Nov 2018. This records a decrease from the previous number of 75,895,261.000 BRL for Oct 2018. Brazil Loans: Real Estate Financing: Value: for Purchase: Residential Building: Market Rate: Southeast: Rio de Janeiro data is updated monthly, averaging 72,112,763.500 BRL from Dec 2009 (Median) to Nov 2018, with 108 observations. The data reached an all-time high of 190,072,704.000 BRL in Jul 2013 and a record low of 22,621,733.000 BRL in Aug 2016. Brazil Loans: Real Estate Financing: Value: for Purchase: Residential Building: Market Rate: Southeast: Rio de Janeiro data remains active status in CEIC and is reported by Central Bank of Brazil. The data is categorized under Brazil Premium Database’s Monetary – Table BR.KAB064: Loans: Real Estate Financing: Value: for Purchase: by Region: Residential Building: Market Rate. The SFH uses the following features to provide credit to citizens: the Guarantee Fund for Time of Service - FGTS (eligible users are allowed the withdraw from FGTS for payment of Real Estate financing under SFH), the current account savings and loans raised in the country or abroad for the implementation of housing projects and mortgage bonds (debt securities) issued by financial agents. Under this scheme, funding can go up to 90% of property value, and cost effective maximum (which includes all charges and expenses incidental to the credit contracted or offered to individuals) may not exceed 12% per year, including interest, fees and other charges. O SFH utiliza os seguintes recursos para fornecer crédito aos cidadãos: o Fundo de Garantia por Tempo de Serviço - FGTS (é permitido o retirar do FGTS para o pagamento de financiamento imobiliário sob SFH), a poupança em conta corrente e empréstimos captados no país ou no exterior para a implementação de projetos de habitação e obrigações hipotecárias (títulos de dívida) emitidas pelos agentes financeiros. Ao abrigo deste regime, o financiamento pode ir até 90% do valor do imóvel, e o custo máximo efetivo (que inclui todos os encargos e despesas acessórias ao crédito contratado ou oferecido a pessoas físicas) não pode exceder 12% por ano, incluindo os juros, taxas e outras encargos.

This table contains the assessed values for current tax year and prior tax year for land and building for properties in Fairfax County. There is a one to one relationship to the parcel data. Refer to this document for descriptions of the data in the table.

Real Estate Across the United States (REXUS) is the primary tool used by PBS to track and manage the government's real property assets and to store inventory data, building data, customer data, and lease information. STAR manages aspects of real property space management, including identification of all building space and daily management of 22,000 assignments for all property to its client Federal agencies. This data set contains PBS building inventory that consists of both owned and leased buildings with active and excess status.

The number of U.S. home sales in the United States declined in 2023, after soaring in 2021. A total of four million transactions of existing homes, including single-family, condo, and co-ops, were completed in 2023, down from 6.12 million in 2021. According to the forecast, the housing market is forecast to head for recovery in 2025, despite transaction volumes are expected to remain below the long-term average. Why have home sales declined? The housing boom during the coronavirus pandemic has demonstrated that being a homeowner is still an integral part of the American dream. Nevertheless, sentiment declined in the second half of 2022 and Americans across all generations agreed that the time was not right to buy a home. A combination of factors has led to house prices rocketing and making homeownership unaffordable for the average buyer. A survey among owners and renters found that the high home prices and unfavorable economic conditions were the two main barriers to making a home purchase. People who would like to purchase their own home need to save up a deposit, have a good credit score, and a steady and sufficient income to be approved for a mortgage. In 2022, mortgage rates experienced the most aggressive increase in history, making the total cost of homeownership substantially higher. Only 15 percent of U.S. renters could afford to become homeowners and in metros with highly competitive housing markets such as Los Angeles, CA, and Urban Honolulu, HI, this share was below five percent. Are U.S. home prices expected to fall? The median sales price of existing homes stood at 387,000 U.S. dollars in 2023 and was forecast to increase slightly until 2025. The development of the S&P/Case Shiller U.S. National Home Price Index shows that home prices experienced seven consecutive months of decline between June 2022 and January 2023, but this trend reversed in the following months. Despite mild fluctuations throughout the year, home prices in many metros are forecast to continue to grow, albeit at a much slower rate.