protsessikaevandamise

Protsessikaevandamine, often translated as process mining, is a discipline that analyzes event logs to discover, monitor, and improve real-world processes. It combines techniques from data mining and process management to provide objective insights into how processes are actually executed, rather than how they are perceived or documented.

The core of process mining relies on event logs, which are digital records generated by information systems as they execute business processes. Each event in a log typically includes a case ID, an activity name, and a timestamp. This data allows process mining algorithms to reconstruct the flow of individual cases through a process.

Key techniques within process mining include process discovery, conformance checking, and enhancement. Process discovery automatically generates a process model from an event log, revealing the actual pathways and variations within a process. Conformance checking compares an observed process execution (from an event log) against a predefined process model to identify deviations. Enhancement aims to improve existing process models by adding insights derived from event logs, such as identifying bottlenecks or analyzing performance metrics.

By applying these techniques, organizations can gain a data-driven understanding of their operations. This understanding can lead to the identification of inefficiencies, compliance issues, and opportunities for optimization. Ultimately, process mining aims to bridge the gap between theoretical process models and their practical implementation, enabling more effective and efficient process management.