Summary

ATTOM Cloud Data

With more than 29.6 billion rows of transactional-level data and more than 9,000 discrete data attributes, the 20TB ATTOM data warehouse powers property data transparency. The following can be used as a guide as to how many records you might encounter when working with property data within ATTOM Cloud.

The following are the numbers when working with the standard trial database

Families

Because our portfolio of property data is so extensive, we have organized it into seven families for easier consumption and understanding: property; transaction; valuation; listing; boundary; school; hazard; neighborhood. In addition, we are developing a series of solution packs that combine this data to solve specific customer needs.

The seven product families are broken down into 50+ data elements. Each data element consolidates data with common characteristics and provides the building blocks from which solution packs are constructed to solve specific

Boundary

A property is defined by a series of coordinates known as a parcel map that forms the outline of the property. Likewise, insights into a property can be gained by understanding the areas into which the property falls. Whether it is a census district, school attendance area, zip code, county, or a flood zone, it can often be useful to visualize these boundaries and the location of the property within it. ATTOM has extensive libraries of boundaries that can be used to visualize these areas or to calculate which properties are located within each.

Hazard

The area in which a property is located is the source of a great many risks that may influence how a property is perceived - its desirability, value, and the range of products and services of interest to owners and occupants.

Neighborhood

Properties are often evaluated in the context of the area in which it is located. Demographics, crime rates, transportation noise, weather, access to public transport, and proximity to points of interest can all form part of a decision to purchase or rental properties and can help companies target markets for their products and services.

Property

The most robust collection of U.S. property data including address details, legal descriptions, zoning uses, house size, lot size, interior features, exterior features, property features, and building permits all compiled in one, easy-to-use database. Real Estate investors, financial institutions, and more use detailed property data to better understand the overall picture of a property. This is complemented with owner details that can be used to communicate your own products and services.

Transaction

ATTOM scours and collates public records and digital databases for transaction and mortgage data. We deliver everything from recorder deed data, loan positions, sales prices, property transfers, and pre-foreclosure, giving you a detailed or holistic picture of the real estate and property market.

Valuation

ATTOM includes assessor data for over 155 million properties and their valuations if included by the county record. Also included is recorder data for more than 430 million transactions covering over 3,140 counties. All this nationwide property data feeds our proprietary Loan Model engine, which generates the estimated loan positions, balances, and equity for a property. ATTOM offers the most flexible selection of robust property data and possesses the strongest property valuation data continuity across various delivery platforms.

Data Element Types

All the data elements that make up ATTOM's extensive library of property data can be broken down into three categories

Point: Data that is tied to a specific property such as Addresses, Assessed Value, Deeds & Mortgages, and Property Characteristics. Some data such as Building Permits, and Deeds & Mortgages may have multiple records for the same property. This data can be accessed via SQL queries and ODBC. Point data is made available via an Azure SQL Server database.

Area: Data that is associated with a geographic area that contains one or more properties. This includes data elements such as census block groups, FEMA flood zones, school districts, and zip codes. Most of this data can be accessed via SQL and ODBC.  ATTOM Cloud includes a lookup table (PropertyBoundaryMatch) that can be used to match point data to area data and vice versa. Shape files that define the shape of the boundaries are currently only available via ATTOM API and Bulk file delivery. Area data is made available via an Azure SQL Server database.

Cube: In some situations, property data can also be presented in a way that supports analysis across multiple types of aggregation and cross-section. Sales Trends is one example. To support this type of analysis, ATTOM publishes this data in a multi-dimension (OLAP) structure supported by many analytics tools such as Excel, Power BI, and Tableau. Cube data is made available via Azure Cube.