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Welcome to Week 2!

Welcome to Week 2!

In the previous week we laid the foundations for this week: we installed the ProM tool and learned what event data and event logs are. We also discussed ways to visualize the event data to start analysing its contents. We also showed how the event data can be filtered.

In this week we discuss the core feature of process mining: discovery of a process model from the (raw) event data.

A process model (for example in the Petri net formalization) describes how activities are related. For instance, the process starts by ‘receive request’, followed by either ‘decline’ or ‘ investigate further’. This is much like the loan application example shown in the previous week.

But how can algorithms discover these process models from raw event data? And which algorithm should I use (since there are several)? And how can I evaluate the resulting process model? You’ll know the answers by the end of this week!

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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
    video

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

  • Installing ProM lite
    Installing ProM lite
    video

    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
    video

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

  • Event logs
    Event logs
    video

    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
    video

    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
    video

    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
    video

    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
    video

    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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