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Welcome to Week 3

Welcome to week 3!

Last week we discussed the core challenge of process mining: how to get from event data to process models.

This week we discuss what we can do when we combine the event data with a process model. Note that this process model can be discovered by an algorithm, but can also be provided as a ‘normative’ model (for instance used to configure the system).

We show how we can detect where the event data and process model agree, and where they don’t. We also discuss how we can project timing information onto process models. In this week we also show how social networks, e.g. how people collaborate within a process, can be discovered.

We also show several process mining case studies, so that you get a feeling of what else is possible with event data and process mining. Finally we also discuss several process mining activities and when these can be applied.

Next week we will apply the algorithms and tools discussed on real data and challenge you to write a process mining report.

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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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