Process mining is a technique that uses data mining and machine learning algorithms to analyze event logs generated by various systems and applications within an organization. The goal of process mining is to discover, monitor, and improve business processes by identifying patterns, bottlenecks, and inefficiencies in process workflows.​

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Process mining works by analyzing event logs to create process models that show how activities are executed, which resources are involved, and how long each activity takes to complete. These models can be used to identify areas where processes can be optimized, such as removing unnecessary steps or reallocating resources to reduce bottlenecks.​

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Process mining can be applied to a wide range of processes, including manufacturing, logistics, healthcare, and finance. The insights gained from process mining can help organizations improve efficiency, reduce costs, and enhance customer satisfaction by identifying areas for process optimization and automation.