EventoWeb
Zürcher Hochschule für Angewandte Wissenschaften
Menu
Home
User Menu
Not registered
Login
[
German (Switzerland)
German (Switzerland)
] [
English
English
]
[
de
de
] [
en
en
]
Not registered
Login
EventoWeb
Kontakt zu Service Desk
Online-Dokumentation
Allgemeiner Zugriff
Module suchen
t.BA.DS.DPS-EN.20HS (Data Products and Services)
Module: Data Products and Services
This information was generated on: 06 December 2024
No.
t.BA.DS.DPS-EN.20HS
Title
Data Products and Services
Organised by
T IDP
Credits
4
Description
Version: 6.0 start 01 February 2024
Short description
The DPS module covers analytical principles for the management of data products and services. Methods for the management of service potentials (e.g. implementation of price differentiation, queue management), service processes (e.g. business process modelling, derivation of business process models from data) and service performance (e.g. modelling of customer lifetime value, implementation of A/B testing) are discussed. In addition, students will be able to implement the presented methods and algorithms in Python using concrete application scenarios and sample data.
Module coordinator
Wulf, Jochen (wulj)
Learning objectives (competencies)
Objectives
Competences
Taxonomy levels
You understand the various challenges of managing data products and services.
F
K2
You will be able to design and implement analytic methodology for managing service potential.
F
K3
You will be able to design and implement analytical methods of process management.
F
K3
You will be able to design and implement analytical methods for managing service performance.
F
K3
Module contents
Fundamentals of data products and services
• Definition and typology of data products
• Definition of services
• Data mining cycle
Data-driven management of service potential
• Queue models, influence of process variability
• Revenue management through price differentiation
• Booking control
Data-driven management of service processes
• Introduction to Process Mining
• Business process modelling with Petri nets
• Process Discovery Approaches
• Methods for measuring process conformity
• Organizational Mining
Data-driven management of service performance
•Approaches to modelling the customer lifetime value (clv)
• Data Envelopment Analysis (DEA)
• Controlled experiments (A/B testing)
Teaching materials
Slides
Supplementary literature
Thonemann, Ulrich. Operations management: konzepte, methoden und anwendungen. Pearson Deutschland GmbH, 2010.
Van Der Aalst, Wil. Process mining: discovery, conformance and enhancement of business processes. Vol. 2. Heidelberg: Springer, 2011..
Prerequisites
Basic knowledge of Python
Basic knowledge of probability theory
Basic knowledge of linear algebra
Basic knowledge of calculus
Teaching language
( ) German (X) English
Part of International Profile
(X) Yes () No
Module structure
Type 2a
For more details please click on this link:
T_CL_Modulauspraegungen_SM2025
Exams
Description
Type
Form
Scope
Grade
Weighting
Graded assignments during teaching semester
Exercises
written
2 lessons
points
20%
End-of-semester exam
Exam
written
90 Min.
Grades
80%
Remarks
Legal basis
The module description is part of the legal basis in addition to the general academic regulations. It is binding. During the first week of the semester a written and communicated supplement can specify the module description in more detail.
Note
Additional available versions:
1.0 start 01 February 2021
,
3.0 start 01 August 2021
,
5.0 start 01 August 2023
Course: Data Products and Services - Vorlesung
No.
t.BA.DS.DPS-EN.20HS.V
Title
Data Products and Services - Vorlesung
Note
No module description is available in the system for the cut-off date of 02 August 2099.