Advancements in information and communication technologies have enabled transit agencies around the world to generate streams of data on a high-frequency basis. Increasingly, these agencies are interested in new methods of visualizing these data to communicate the results of their planning efforts, operational investments, and overall transit performance to decision makers and stakeholders. Most agencies today collect and provide numerous kinds of data, including Google’s general transit feed specification schedule data, automatic vehicle location data, and automatic passenger count data. This paper aims to demonstrate the untapped potential of these data sources; specifically, the paper uses transit data from Montreal, Quebec, Canada, to generate performance measures that are of interest to both transit planners and marketing professionals. Some of these measures can also help in communicating the positive attributes of public transportation to the community. Performance measures are generated at different scales, including transit system, neighborhood, route, and stop levels. This paper expands on previous research on transit performance research and visualization by adopting currently available resources for so-called big data.