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Process mining is a family of techniques for analyzing event data 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 ...
Business process discovery (BPD) related to business process management and process mining is a set of techniques that manually or automatically construct a representation of an organisations' current business processes and their major process variations. These techniques use data recorded in the existing organisational methods of work ...
The outer circle in the diagram symbolizes the cyclic nature of data mining itself. A data mining process continues after a solution has been deployed. The lessons learned during the process can trigger new, often more focused business questions, and subsequent data mining processes will benefit from the experiences of previous ones.
A set of solution add-ons that include collections of task-oriented templates and vector stencils libraries, [5] have been released for ConceptDraw DIAGRAM, relating to certain industry-specific graphical tasks. Starting with version 11, DIAGRAM supports using the LaTeX typesetting system in formulas and text. [6]
These elements are used in event-driven process chain diagrams: Event Events are passive elements in event-driven process chains. They describe under what circumstances a function or a process works or which state a function or a process results in. Examples of events are "requirement captured", "material in stock", etc.
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