The article discusses Process Mining technology as an effective tool for bridging the gap between regulatory business process models and empirical data on their actual execution. It analyzes the key stages of process-oriented data analysis, including process discovery, compliance verification, and process improvement. Special attention is given to the event log as the methodological foundation of Process Mining, as well as modern software tools such as Celonis, UiPath, and ABBYY Timeline. Using the example of equipment repair, a comparative analysis of three model building algorithms was performed: the alpha algorithm, Heuristics Miner, and Inductive Miner. The advantages and disadvantages of each algorithm were identified, and recommendations for their practical application were formulated. Current challenges in implementing the technology and future research prospects were outlined.
business process analysis, event logs, process discovery, conformance checking, process enhancement
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