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Big data, with its four main characteristics (Volume, Velocity,
Variety, and Veracity) pose challenges to the gathering, management, analytics, and visualization of events. These very same four characteristics, however, also hold a great promise in unlocking the story behind data. In this talk, we focus on the observation that event creation is guided by processes. For example, GPS information, emitted by buses in an urban setting follow the bus scheduled route. Also, RTLS information about the whereabouts of patients and nurses in a hospital is guided by the predefined schedule of work. With this observation at hand, we thoroughly seek a method for mining, not the data, but rather the rules that guide data creation and show how, by knowing such rules, big data tasks become more efficient and more effective. In particular, we demonstrate how, by knowing the rules that govern event creation, we can detect complex events sooner and make use of historical data to predict future behaviors.