Recent technological advances provide new opportunities for transportation professionals to retrieve and analyze large quantities of travel related data, often from location-based services (LBS) on mobile devices, connected vehicle data, and/or GPS navigation units. The “Big Data” come in large volumes, at a higher speed, from a variety of sources, with varying levels of accuracy and reliability. Because they are large and complex, analytical tools are often needed to analyze and visualize the data. There are several vendors that currently provide a variety of traffic data, including O-D, multimodal traffic volumes, travel speeds, travel times, trip trajectory, and even turning movement volumes. It is important to note that both “traditional data” and “Big Data” are sample data. Traditional data, such as link counts, and turning movement counts, sample all people on some days, whereas “Big Data” sample some people on all days. Because they are all sample data, caution must be exercised when using the data to make sure they are consistent with real-world ground conditions. Different vendors use different methodologies to “factor up” original data to represent traffic parameters for the entire population. It is advisable to understand the algorithms and validate the data before using “Big Data” for travel demand forecasting.