This paper proposes the estimation of trip origin-destination matrices using big data through two case studies. In the first, trip matrices are estimated from mobile network data and compared with household travel survey results. In the second, public transport trip matrices are derived from smart card data and compared with passenger survey data. The paper concludes that sample size and longitudinal data collection are big data’s main strengths, yet are limited by privacy protection constraints and by the need to control for biases in the sample.