Business Process Analytics in R

Business Process Analysis 

Made easy with bupaR

bupaR is an open-source, integrated suite of R-packages for the handling and analysis of business process data. bupaR provides support for different stages in process analysis, such as importing and preprocessing event data, calculating descriptive statistics, process vizualisation and conformance checking. 

Analyse every perspective of your process

From the control-flow, over performance, to organisational aspects – bupaR gives you the flexibility you need to look at your process data from any angle you like. Custom process attributes can be included effortlessly into your analysis workflow. 


bupaR is an excellent set of R packages that allows you to visualise and summarise your processes. With the help of a wide range of useful functions, you can easily analyse the activities under your processes and generate quick insights. These highly customizable functions also let you focus on the analysis itself by saving data manipulation time. As an analyst, the “process maps” and the “trace explorer” charts are two of my favourites which allows me to communicate the overall picture with the audience effectively. 

Kazım Albayrak

Data Scientist, Aegon

With bupaR I can analyze processes at scale as they happen. This is helping me understand processes at my company in greater detail and identify areas that may be candidates for optimization. The fact that bupaR is an open source R package means I can easily replicate my analysis to monitor the impact of change. Many thanks to all who have contributed to the development and maintenance of bupaR!

Nirmal Patel

Chief Data Scientist, Playpower Labs

I found bupaR by imagining an ideal R package for processing and displaying data into process maps. The packages did more than I expected them to do, with very simple code. The process diagrams have been incredibly useful at getting qualitative focused colleagues and the process users engaged with and trusting the data. It is a good resource to have when working with complex healthcare datasets and has given me a new insight into working with them.

Peter Pensotti

Process Architect