Year of Graduation
Automated Analysis of the Business Process Using Process Mining
Applied Mathematics and Information Science
Modern information systems (for example, class systems ERP, CRM, BPM) are widely used in various companies, recording events of business processes occurring in companies in the so-called event logs. The obtained data are further analyzed in order to study the process more thoroughly, to reveal its structure, and also the possibility of optimization. At present, software for analyzing business processes is developed and continues to be developed. However, the functionality of the solutions used is usually reduced to a convenient interface for working with event logs, visualizing them and counting some metrics, direct analysis, while conducting a specialist. Therefore, one of the areas of development of the analysis of business processes is automation, in particular, the application of methods of machine learning ——- science, dedicated to the identification of various patterns in data sets. This work is mainly focused on studying the application of algorithms and machine learning approaches in the field of business process analysis. The goal of the project is to develop software for visualization, calculation of KPI, construction of predictive models for improving and automating the analysis of business processes.