Accounting for non-resident travel in the context of regional travel modeling is a challenge. While this market is small in relation to resident travel, it must, nonetheless, be accounted for in order to achieve acceptable matches between simulated network link volumes and traffic counts. Traditional methods to collect information about non-resident travel, such as auto intercept surveys, are falling out of favor with planning agencies, given their high costs and high non-response rates. As an alternative, planning agencies have begun considering “Big Data” solutions to address information needs. The staff the Metropolitan Washington Council of Governments/National Capital Region Transportation Planning Board (MWCOG/TPB) has recently purchased cellular origin-destination (O-D) data from one Big Data provider for the purpose of updating non-resident travel forecasting processes for the Washington, D.C. region. Because this type of information source is novel, staff has conducted an evaluation of the data. This paper describes the cellular data we have obtained and presents comparisons of the data with travel model outputs, land activity and traffic counts. The comparisons are useful for understanding how cellular O-D information differs from modeling data with which most planners are familiar.