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This paper focuses on the most critical task in monitoring and control of power systems: converting data to knowledge that will facilitate control action. With expansion of smart grids, which assume wide dissemination of intelligent electronic devices (IEDs) in substations supported by extensive communications, data associated with power system events becomes abundant. The fact that new data of better quality than before exists in smart grids does not assure that better decision making will be possible. In order to convert data to actionable knowledge, certain processing needs to be performed. This processing is referred to as Translational Knowledge, i.e., the knowledge that allows transition from data collection to action. This concept is illustrated through several applications such as fault locating, alarm processing, and protective relaying.