ER 2021 Tutorial - Process Mining: Turning Event Data Into Conceptual Models by prof.dr.ir. Wil van der Aalst
This is a preparation video for the tutorial at the 40th INTERNATIONAL CONFERENCE ON CONCEPTUAL MODELING (ER 2021), 18-21 October 2021 St. John's, NL, Canada.
Short description
Process mining is the missing link between model-based process analysis and data-oriented analysis techniques. Through concrete data sets and easy-to-use software, the tutorial provides concepts and tools that can be applied directly to analyze and improve processes in a variety of domains.
The course explains the key analysis techniques in process mining. Participants will learn about process discovery techniques. These can be used to automatically learn process models from raw event data. Various other process analysis techniques that use event data will be presented, including conformance checking. Moreover, the course will provide access to easy-to-use software, real-life data sets, and practical skills to directly apply the theory in a variety of application domains.
The course is relevant for ER participants because there is a direct connection to conceptual modeling. A conceptual model is a representation of a system or process, made of the composition of concepts which are used to help people to better know, understand, simulate, and improve the system of process the model represents. In the context of the larger Business Process Management space, conceptual models play an important role. See, for example, the Business Process Modelling Notation (BPMN) notation and the process-oriented diagrams in UML (activity diagrams, statecharts, sequence diagrams, class diagrams, etc.). It is not just about the modeling of processes but also the data.
Process mining provides a range of techniques to relate data in information systems to conceptual models. In recent years, we could witness a spectacular uptake in process mining. There used to be a gap between process science (i.e., tools and techniques to improve operational processes) and data science (i.e., tools and techniques to extract value from data). Mainstream machine learning and data mining techniques do not consider operational processes. Business Process Management (BPM) and Operations Research (OR) tend to start from models rather than data. Process mining bridges this gap. Currently, there are over 35 commercial process mining vendors (ABBYY Timeline, ARIS Process Mining, BusinessOptix, Celonis Process Mining, Disco/Fluxicon, Everflow, Lana, Mavim, MPM, Minit, PAFnow, QPR, etc.) and process mining is applied in most of the larger organizations. Example application domains include: finance (Rabobank, Hypovereinsbank, etc.), telecom (Deutsche Telekom, Vodafone, etc.), logistics (Vanderlande, etc.), production (BMW, Siemens, Fiat, Bosch, etc.), food (Edeka, etc.), fashion (Zalando, etc.), energy (E-on, etc.), transport (Uber, DB, Lufthansa, etc.), healthcare (AstraZenica, Medtronic, etc.), consulting (Deloitte, EY, KPMG, etc.), and IT systems (Dell, IBM, ServiceNow, etc.).
Target audience, prerequisite knowledge, and learning goals
Process mining provides not only a bridge between data mining and business process management; it also helps to address the classical divide between "business" and "IT". Evidence-based business process management based on process mining helps to create a common ground for business process improvement and information systems development. Therefore, the tutorial is interesting for participants that are interested in both technical aspects and applications.
The tutorial will be at an introductory level. Participants should have a basic understanding of process and data modeling without knowing a specific notation or language.
Tutorial contents and structure
The ER tutorials consist of a prerecorded introductory video (about 1h) and an interactive session (1h) given online. Pointers to additional material will be given. Note that the lecturer has created several longer online courses, including the "Process Mining: Data Science in Action" Coursera course with over 135.000 participants.
The prerecorded introductory video explains the basic concepts of process mining both from a bottom-up and top-down perspective. Keywords are event data, cases, activities, timestamps, process perspectives, control-flow, process discovery, conformance checking, decision mining, etc.
Participants are encouraged to download the provided process mining software and data sets after watching the prerecorded session.
The online session will provide smaller examples and show the application of both open-source and commercial software to the data sets provided.
Links:
- www.vdaalst.com
- www.processmining.org
- www.promtools.org
- https://www.celonis.com/academic-signup/
- https://www.coursera.org/learn/process-mining