Process mining is a family of techniques used to analyze event data in order to understand and improve operational processes. Part of the fields of data science and process management, process mining is generally built on logs that contain case id, a unique identifier for a particular process instance; an activity, a description of the event that is occurring; a timestamp; and sometimes other information such as resources, costs, and so on.[1][2]
There are three main classes of process mining techniques: process discovery, conformance checking, and process enhancement. In the past, terms like workflow mining and automated business process discovery (ABPD)[3] were used.