Moses - Process Mining

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Diese Modulbeschreibung gilt nicht im aktuellen Semester.

Die Modulbeschreibung gilt nur für den Zeitraum WiSe 2022/23 - SoSe 2023.

Module / Version:
#40990 / #3

Validity:
WiSe 2022/23 - SoSe 2023

Default display language:
English

Module title:
Process Mining

Credits:
6

Responsible person:
Pufahl, Luise

Grading:
benotet

Type of exam:
Portfolioprüfung

Zugehörigkeit

Faculty:
Fakultät IV

Institute:
Institut für Wirtschaftsinformatik und Quantitative Methoden

Area of expertise:
34361500 FG Software and Business Engineering

Prüfungsausschuss:
No information

Kontakt

Office:
EN 6

Contact person:
Pufahl, Luise

E-mail address:
pm@sbe.tu-berlin.de

Website:

https://www.sbe.tu-berlin.de/menue/lehre/lehrveranstaltungen/

Learning Outcomes

After successfully completing this course, students will be able to: - explain the principles of process mining and its application area - understand the structure of event logs (the basic input for process mining) and how it is generated - know basic process mining algorithms for the different perspectives: discovery, conformance, and enhancement, and their limitations - how to run a process mining project - present results of a data-driven project in a written and oral format.

Content

Process mining is a family of new data analysis methods that aims to discover, monitor, and improve business processes and is increasingly adopted by the industry. It analyses so-called event logs, which capture the real execution data of business processes, and are usually collected from one or several information systems supporting the execution of business processes. The main difference from traditional data analysis techniques is that process mining focuses on the process perspective. It aims to reveal the complex order relations among the activities captured in the event log. This lecture gives an introduction to the field of process mining. After introducing basic formalisms, the lecture provides a detailed and algorithmic perspective on the three key process mining perspectives: process discovery, conformance checking, and enhancement. Furthermore, it is discussed how typically process mining projects are executed. Finally, the lecture shows how process mining is currently used in industrial environments.

Module Components

Pflichtgruppe:

All Courses are mandatory.

Course Name	Type	Number	Cycle	Language	SWS	VZ
Process Mining	IV	3436 L 10596	WiSe/SoSe	English	4

Workload and Credit Points

Process Mining (IV):

Workload description	Multiplier	Hours	Total
Attendance (lecture + lab)	10.0	4.0h	40.0h
Pre/post processing	10.0	8.0h	80.0h
Project	1.0	60.0h	60.0h
			180.0h(~6 LP)

The Workload of the module sums up to 180.0 Hours. Therefore the module contains 6 Credits.

Description of Teaching and Learning Methods

Lectures, assignments, and a project: - Participation from students is expected, and attendance will be of tremendous value towards successful completion. - Assignments are used to self-study the learned material and for a practical application of the introduced techniques. Students are asked to actively participate in the assignment discussion and prepare for the written exam. - The project will mimic a real-world project, and provide practical experiences in running a process mining project.

Requirements for participation and examination

Desirable prerequisites for participation in the courses:

This module assumes advanced computer science / information systems management skills. Before commencing this course, students should - have solid programming background - know basics of business process management.

Mandatory requirements for the module test application:

This module has no requirements.

Module completion

Grading

graded

Type of exam

Portfolio examination

Type of portfolio examination

100 Punkte insgesamt

Language

German/English

Test elements

Name	Points	Categorie	Duration/Extent
(Examination) Final exam	50	written	60 min
(Deliverable assessment) Project presentation	20	oral	20 min
(Deliverable assessment) Project report	30	written	8-15 pages

Grading scale

Notenschlüssel »Notenschlüssel 1: Fak IV (1)«

Gesamtpunktzahl	1.0	1.3	1.7	2.0	2.3	2.7	3.0	3.3	3.7	4.0
100.0pt	86.0pt	82.0pt	78.0pt	74.0pt	70.0pt	66.0pt	62.0pt	58.0pt	54.0pt	50.0pt

Test description (Module completion)

No information

Duration of the Module

The following number of semesters is estimated for taking and completing the module:
1 Semester.

This module may be commenced in the following semesters:
Winter- und Sommersemester.

Maximum Number of Participants

The maximum capacity of students is 30.

Registration Procedures

Course registration will be organized through ISIS, and happen in the first week of the semester.

Recommended literature
Ralf Laue et al. Prozessmanagement und Process Mining, De Gruyter Oldenbourg 2021
Wil van der Aalst. Process Mining: Data Science in Action. Springer 2016
Josep Carmona et al. Conformance Checking: Relating Processes and Models. Springer 2018
Marlon Dumas et al. Fundamentals of Business Process Management, 2nd edition. Springer 2018

Assigned Degree Programs

Semester:

Zeige auch ausgelaufene Studiengänge und StuPOs

This module is used in the following Degree Programs (new System):

	Studiengang / StuPO	StuPOs	Verwendungen	Erste Verwendung	Letzte Verwendung
This module is not used in any degree program.

Miscellaneous