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This content is taken from the Eindhoven University of Technology's online course, Introduction to Process Mining with ProM. Join the course to learn more.

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!

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!

Eric Verbeek - Lead educator

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This article is from the free online course:

Introduction to Process Mining with ProM

Eindhoven University of Technology

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