This thesis deals with the increasingly pervading concept of Big Data and its potential to become an integral part of maritime shipping- like it has in other industries such as healthcare and banking. Big Data is a topic that covers a wide array of different areas, and to this end, the thesis outlines the core framework of Big Data and how this framework can be adopted in the maritime shipping industry. In doing so, the thesis defines maritime Big Data and illustrates one use of such data through the employment of AIS (Automatic Identification System) data. Empirically, the thesis demonstrates the ability of AIS data to analyse commodity flows, and how such applications can be useful to shipping players such as charterers and ship owners. The empirical studies suggest that maritime Big Data like AIS data can be of high value to the maritime shipping industry- particularly as part of a larger context and with the development of a clearer regulatory landscape for Big Data in the industry.