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Welcome to the course!

Hi, and welcome to the course ‘Process mining with ProM’. In this course we will teach you how to install and use the free and open source process mining tool ProM lite. At the end of this course you will be able to recognise event data, convert it into an event log, and analyse the underlying process using the process mining tool ProM.

Coming up this week

This week we start with explaining what process mining is, and where you can find event data (hint: everywhere!).

Next we explain how to install ProM lite, so please have a computer ready. We also have a full video on the basic usage of ProM (or: “what do all the buttons do?”).

We also provide plenty of pointers for further information, as well as a discussion where we would like to hear if you encountered any issues, and where you can ask fellow learners for assistance.

Event logs

With this course comes a collection of open and free to use event logs. This collection contains both artificial (e.g. generated) data, but also real data from real systems. This data we use throughout the course in the videos, quizzes, test, and finally in the peer assignment. However, we do not use all provided data sets, so some are for you to explore on your own!

In this week we will also discuss what event data, stored in an event log, looks like, and also how you can load and inspect an event log in ProM lite.

Of course, data is not stored in nice event logs, and usually has to be converted. We show you how you can use ProM lite to convert a CSV file to an event log. After the raw data is in ProM lite, we can explore its contents. Additionally, we usually also need to filter the data to gain better insights.

So, at the end of this week you will already know how to get and inspect the event data in ProM lite. Next week we will show you how you can discover process models from this data, which describe the behavior stored in the data.

Throughout the course we hope you see for each step the practical applications. We also hope, and encourage you, to start and join the discussions, and to help each other if you see someone is stuck. We will join in as well as much as we can, but the best teaching and most interesting discussions are between you and your peers!

Please also remember you have the option to buy a Certificate of Achievement to prove what you’ve learned on this course. Alternatively, you can buy a Statement of Participation as a memento of taking part.

The money from the sale of Certificates and Statements supports the development of FutureLearn and free online courses.

Finally, we would really like to encourage you to fill in the pre-course survey. This helps us, and FutureLearn, to improve this course for future learners.

We hope you enjoy following this week as much as we did making it!

Joos Buijs - Lead educator

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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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