Like most IT-related phenomena, also the growth of event data complies with Moore’s Law. Similar to the number of transistors on chips, the capacity of hard disks, and the computing power of computers, the digital universe is growing exponentially and roughly doubling every 2 years. Although this is not a new phenomenon, suddenly many organizations realize that increasing amounts of “Big Data” (in the broadest sense of the word) need to be used intelligently in order to compete with other organizations in terms of efficiency, speed and service. However, the goal is not to collect as much data as possible. The real challenge is to turn event data into valuable insights. Only process mining techniques directly relate event data to end-to-end business processes. Existing business process modeling approaches generating piles of process models are typically disconnected from the real processes and information systems. Data-oriented analysis techniques (e.g., data mining and machines learning) typically focus on simple classification, clustering, regression, or rule-learning problems. This keynote paper provides pointers to recent developments in process mining thereby clearly showing that process mining provides a natural link between processes and data on the one hand and performance and compliance on the other hand.