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Welcome to Week 4

Welcome to Week 4, which has a different set-up compared to the other weeks. By now you know how to operate ProM, how to load and explore an event log, and how to discover a process model. This week we will collaboratively apply what we have learned to analyse a real-life event log.

The event log that we use during this week is the ‘Road_Traffic_Fine_Management_Process.xes.gz’ in the provided event log zip file. This event log contains events related to handling road fines by an Italian police department.

During this final week we will first together discover the contents of the event log, using the log dialog and dotted chart, for instance. Together we will try to find one or more ways to filter the event log, to prepare it for the main step of this week: discovering a process model.

Using one of the filtering approaches suggested in the discussion, you are asked to discover a process model and analyse its conformance on the (filtered) data. This will be done in the form of a peer assignment, so an individual assignment.

After you have submitted your peer assignment, you are asked to evaluate one or more submissions from your peers. After which you can discuss the assignment with your peers.

Then we follow with a discussion on what we can do with these process models. In Week 3 we have learned that we can project performance information on the process models. What information does this provide us?

We have also learned to analyse the social aspects of the process. We will apply the techniques we learned and discuss what we can find.

This week is concluded by a discussion, where we summarize our findings and recommendations to the process owner.

We hope that this week will provide you with additional insights and the knowledge to perform a process mining analysis individually.

Looking forward to your findings! And happy mining :)

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This article is from the free online course:

Introduction to Process Mining with ProM

Eindhoven University of Technology

Get a taste of this course

Find out what this course is like by previewing some of the course steps before you join:

  • Introduction

    Introduction to process mining: recognizing event data, what is process mining and what can process mining analyse.

  • Installing ProM lite
    Installing ProM lite

    In this step we show how to find and install the free and open source process mining tool ProM lite.

  • Using ProM lite
    Using ProM lite

    In this lecture we show the basic concepts and usage of ProM (lite): the resource, action and visualization perspectives.

  • Event logs
    Event logs

    In this lecture we explain what an event log is and how it is structured. We also explain the most common attributes found in an XES event log.

  • Event logs in ProM
    Event logs in ProM

    In this lecture we show you how you can load an event log in ProM and how you can get initial insights in the contents.

  • Converting a CSV file to an event log
    Converting a CSV file to an event log

    Most data is not recorded in event log format. In this video we explain how a CSV file can be converted to an event log.

  • Exploring event logs with the dotted chart
    Exploring event logs with the dotted chart

    After loading an event log into ProM it is important to apply the dotted chart to get initial process insights before process models are discovered.

  • Filtering event logs
    Filtering event logs

    Before good quality process models can be discovered the event log data needs to be filtered to contain only completed cases for instance.

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