Protsessikäsitlus

Protsessikäsitlus, also known as process mining, is a field of data science that focuses on extracting knowledge from event logs. These logs record the activities performed within a process, such as those executed by a workflow management system, a business process management system, or any software system that logs events. Process mining aims to discover, monitor, and improve real processes by extracting knowledge from event logs.

The primary goal of process mining is to bridge the gap between model-based process analysis and data-oriented analysis techniques. It provides a middle ground where both the model and the data are used to understand and improve processes. Process mining techniques can be categorized into three main types: discovery, conformance, and enhancement.

Discovery techniques focus on creating process models from event logs. These models can be used to understand how processes are actually executed, which can reveal inefficiencies or deviations from expected behavior. Conformance checking techniques compare an existing process model with event logs to check if the model is being followed as expected. Enhancement techniques extend or improve an existing process model using information from the event logs.

Process mining has applications in various fields, including business process management, healthcare, manufacturing, and software engineering. It helps organizations to identify bottlenecks, optimize processes, and ensure compliance with regulations. By providing insights into how processes are actually executed, process mining can lead to significant improvements in efficiency, quality, and compliance.