t.BA.DS.DPS-EN.20HS (Data Products and Services) 
Module: Data Products and Services
This information was generated on: 24 July 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

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.