Abstract
In the current context of availability of large amounts of data (Big Data), its underlying value can be, frequently, devalued. However, there are several tools that allow to extract knowledge from data. Among other information, this knowledge can lead to improve processes or detect any failure during their execution. This work intends to compare several process mining (PM) tools, using different techniques. For each tool, the best scenario in the discovery of processes is found and the respective results are evaluated. The results showed that Disco is the simplest and most intuitive tool to use. Along with ProM, it also allows a complete analysis, without the need for theoretical knowledge concerning PM or programming. PM4Py, on the other hand, is a free framework that allows great customizations for all functionalities. So it is ideal for professionals with knowledge in PM needing more adjusted implementation or integration with other applications. From a cost perspective, either PM4Py or ProM are free. The use of PM4Py can be complemented by ProM for compliance verification.
Recommended Citation
Gomes, André Filipe Domingos; Wanzeller, Cristina; and Fialho, Joana, "Comparative Analysis of Process Mining Tools" (2021). CAPSI 2021 Proceedings. 4.
https://aisel.aisnet.org/capsi2021/4