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Business Process Analytics

In this course, you learn the essentials of business process analytics.

About This Course

Business processes are widely recognized as the drivers of organizational performance. It is through efficient and effective processes that companies achieve low costs, high levels of business agility, low waiting times and high and consistent quality. Consequently, business process management has become a core capability of many successful organizations.

Today, as we have entered the age of big data, business process management can be taken to the next level. Besides traditional types of data - e.g. financial, sales, customer or production data - companies increasingly collect large amounts of process data which describe how processes are being executed at a detailed level. The combination of process data with the power of business process analytics enables data-driven and evidence-based business process management at a level that was previously unthinkable.

This course provides the essential foundation for those who want to get started with business process analytics in order to improve business processes in an objective and data-driven manner. You will gain a thorough understanding of the most important concepts and techniques of process analytics, discover which analyses can be applied, how these can be visualized and learn how to interpret and translate process analytics into deeper insights of how an organization actually works. Throughout the course, concepts and techniques are put into practice through a series of examples, situated in various fields.


The enrollment fee for this course is EUR 100 (VAT excl.) per participant. Payments are securely handled by PayPal. If you are a company in the European Union, then we can apply VAT reverse charge. For this, please mail your VAT number to Part of our course revenue is used towards funding organizations involvement in protecting and cleaning our oceans. See our about page to learn more about our mission statement.

After enrollment, participants will get 1 year unlimited access to all course material (videos, quizzes and certificate).


Before subscribing to this course, you should have a basic understanding of descriptive statistics (e.g., mean, median, standard deviation, histograms, scatter plots, etc.) and inference (e.g., confidence intervals, hypothesis testing).

Course Outline

    Introduction Process oriented thinking and Process Analysis
  • BPM Lifecycle
  • From confidencebased to evidencebased BPM
  • Process Analytics Terminology
  • Different goals: understanding (“discovery”) and controlling (compliance/conformance)
  • Different perspectives: controlflow/organisational/time/cost
  • Tools for process analytics
    Process analysis with bupaR (R)
  • Understanding Processes
  • Process maps
  • Dotted charts
  • Resource roles
  • Process Metrics (performance, structuredness)
  • Controlling processes
  • Filtering
  • Rule checking
  • Resource restrictions
  • Process data wrangling
  • Aggregation
  • Enriching
  • Analysing complex research questions
  • Combining different perspectives
  • Concept drift
  • Advanced Algorithms
  • Process discovery
  • Alignments
    Getting started
  • How to structure your process analytics project?
  • Event log building
  • Business process analytics case studies


Before subscribing to this course, you should have a basic understanding of descriptive and exploratory statistics (e.g., mean, median, standard deviation, histograms, scatter plots, etc.) and have a basic notion about business processes. Previous R experience is recommended, but not necessary.

Course Staff

Course Staff Image #1

Prof. dr. Benoît Depaire

Benoît, with a circumflex on the penultimate letter as his mother insisted on when he was born, currently lives in rural As (Limburg, Belgium) with his wife and two sons. He was born and raised in the Maas Valley at the eastern border with the Netherlands, in a picturesque little town Leut. As most people from this region, he highly values strong friendships, the small things in life and the local community, and possesses the ability to be notoriously stubborn at times (which he equally stubbornly denies). His passions are being a father, preparing and experimenting with food and all IT-related things. A Saturday at the football pitch watching his sons play, an evening dinner with friends trying out a new dish or a Sunday afternoon programming a hobby project are key ingredients for his perfect weekend.

Benoît is an Associate Professor Business Informatics at Hasselt University within the faculty of Business Economics, where he is head of the Business Informatics program. He strongly believes that new technologies are a prerequisite for many modern day innovations in business and society. However, he likes to argue that the true potential of IT does not lie in the technology itself, but in the way we use it to create value. Understanding how to unlock this potential and sharing these insights is the ultimate goal to which he tries to contribute. He does this on a daily basis, together with his colleagues of the research group Business Informatics at Hasselt University.

To this end, he recently took the lead in setting up the applied research unit BIARU ( BIARU is a dedicated team of researchers whose goal is to disseminate the research group’s expertise in data analytics, business process management and machine learning to a larger audience. Building on decades of expertise in data modelling, data mining, process management and process mining, BIARU provides two services, always founded in scientific rigor and academic independence. Firstly, BIARU offers various training programs to broaden the data science knowledge and skills of their partners. Secondly, by way of projects BIARU works together with their partners from problem to solution.

Benoît’s current research focuses on the science of algorithm engineering and behavioral analytics. Behavioral analytics is a recent advancement in business analytics that reveals new insights into the behavior of consumers, employees, machines, processes and systems. The goal is to extract behavioral and actionable insights from fine grained data. Applied to the context of business processes, which has been the focal point of Benoît’s research over the past decade, this strongly connects to the field of process mining. Benoît’s research has been presented at various international conferences and published in journals such as Intelligent Data Analysis, Business and Information Systems Engineering, Computers in Human Behavior, Decision Support Systems, Information Systems, Knowledge-based Systems and IEEE Transactions on Services Computing.

Course Staff Image #2

Prof. dr. Mieke Jans

Mieke was born in Hasselt and currently resides in Genk, where she lived her entire life. The only other link with Hasselt is the university where she is employed, already since 2003. Other than that: Genk will remain favourite over Hasselt to Mieke. Mieke is married and has a terrific daughter and son with a mean age of 10. Mieke started her PhD because it was a job where she would actually get paid for being critical, asking annoying questions, and investigating things profoundly. Things that aren’t always appreciated in ‘the real life’. The journey led to a PhD, earned in 2009 (at Hasselt University) with her research on the use of data mining and process mining techniques for the purpose of internal fraud risk reduction. From 2009 until 2014, Mieke paused her personal life by combining working in industry with working in academics. Being employed as a (senior) manager at Deloitte Belgium, she was part of the data analytics cell and Belgian lead of Process Mining applications. In parallel, she was part-time affiliated with Hasselt University to teach amongst other courses Business Process Analytics. After returning full-time back to academics, Mieke gradually found time to reinstall what she loves outside of work: running and mountainbiking. Mieke likes reading, but is terrible in making time for it, and she is also a true Belgian: she just loves french fries (and hates it is called like that in English). She loves French wine though (Merlot, Chardonnay…), but also other grapes (Shiraz, Negoramaro...). And chocolate. Of course...

Mieke is now associate professor Business Informatics at Hasselt University, Belgium. She is active in the research field of Accounting Information Systems, which is translated into a part-time appointment at the School of Business Economics, Maastricht University in the Accounting and Information Management department. Since September 2014, Mieke researches how process mining could add value to the auditing profession. Bridging the Business Informatics research group of Hasselt University and the Accounting and Information Management group of Maastricht, allows Mieke to research ‘Audit Analytics’, primarily but not exclusively from a process point of view. For this topic, she works closely together with industry and established researchers both in the Accounting field as in the Business Process Management / Information Systems field. By moving focus from the accounting to the BPM/IS area, Mieke’s research outlets, along with her community servicing tasks, span over different research fields.

Mieke is founder of the Scientific Research Community on Process Mining (since 2017) and is member of the steering committee of the IEEE Task Force on Process Mining. Since 2019, she has also been appointed associate editor of the International Journal of Accounting Information Systems. Her work has been published, amongst others, in The Accounting Review, Journal of Information Systems, Enterprise Information Systems, International Journal of Accounting Information Systems, and Expert Systems with Applications. She is regularly invited as guest lecturer on process mining in different (auditing) programs, for example at Erasmus University.

Course Staff Image #2

dr. Gert Janssenswillen

Gert was born in Lommel (Limburg, Belgium) on June 28th, 1991. He currently lives in Hasselt - Capital of Taste (, where he is a self-proclaimed local city guide. In his spare time he is a fervent reader of books ( - in particular on history, geography, and psychology. Apart from reading about them, he loves travelling to historical places to discover ancient times. At home, he is an ardent hiker and biker in the local natural reserve areas. In the evenings, he likes to enjoy a nice strong beer (preferably Belgians).

Gert Janssenswillen is a postdoctoral researcher on process analytics at Hasselt University, Belgium. In 2019 he obtained a PhD in process mining, which focussed on the quality measurement of process mining algorithms in the context of conformance checking. During his PhD he created bupaR - a collection of R packages for process analysis, of which he is still the main contributor ( Gert has shared his research as a speaker at various conferences, such as BPM, SIMPDA and useR, and author of articles in international journals, such as Information Systems, Knowledge Based Systems, and Business Information Engineering Systems.

As one of the researchers in the area of conformance checking within process mining, he organized a brainstorm on research challenges in 2018, and is co-guest-editor of a Special Issue on Conformance Checking for the Information Systems journal. Furthermore, he is co-organizer of the recently founded Conformance Checking Challenge, organized in the margin of the International Conference on Process Mining (ICPM). Gert’s research experience includes process analytics projects in a broad range of fields, including operational excellence, logistics and learning analytics. At Hasselt University he teaches courses on Exploratory and Descriptive Data Analysis and Business Process Analytics.