Take out your helmets and shovels because we've arrived at the mines (of our processes)! During this stop, we will reuse the process created at the ACME Bank (Stop #2) and discover the exciting world of Process Mining. With the help of our guest conductor Nour Assy, we will learn how to retrieve the execution data of our process, analyze it and optimize our processes!
Questions Answered During this Session
- What is Process Mining?
- Is it possible to start with Process Mining even if we don't use the BPMN approach?
- How can I identify the bottlenecks in my processes?
- How can I know what is the cause of a bottleneck on my process?
- Is it possible to anticipate and prevent bottlenecks?
- Which data is required for Process Mining?
- Is there a requirement in terms of data format?
- How can I retrieve the execution data of my processes?
- What is the goal of the Process Analytics project?
- Which technical environment is preferred for Process Mining?
- Which technologies does the Process Analytics project use?
- Which are the different techniques in Process Mining?
- What is the difference between Process Mining and Data Mining?
- Are there any Process Mining tools already integrated in Bonita?
Useful links shown during this session
- Process Mining Visualization Libraries: https://process-analytics.dev/
- Live Demos and Examples using Process Analytics: https://cdn.statically.io/gh/process-analytics/bpmn-visualization-examples/master/examples/index.html
- API Documentation on Archived User Tasks: https://api-documentation.bonitasoft.com/latest/#tag/ArchivedUserTask/operation/searchArchivedUserTasks
- Open-source Process Mining libraries:
- bupaR: https://bupar.net/
- pm4py: https://pm4py.fit.fraunhofer.de/
- Process mining open source tools:
- ProM (https://promtools.org/)
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