Data Analytics and Decision-Making

M.Sc.|MBA|Micro Degree BDAI_dataanalytics

This module teaches advanced data analysis for decision-making. Students learn to differentiate between descriptive, diagnostic, predictive, and prescriptive analytics and their business applications. It covers theoretical concepts and practical approaches to objective analysis and decision-making.

Course Start:
Course End:
Estimated Effort:
10:00 h/week

Book Micro-Degree Program Enrollment in this course is by invitation only*

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Data Analytics and Decision-Making

About This Course

This module provides advanced knowledge about the structure and analysis of large amounts of data and how this is to be used in decision-making processes. Students learn the difference between descriptive, diagnostic, predictive and prescriptive analytics and their application in business contexts. In the module, theoretical concepts and approaches of objective analysis and decision-making are covered.

Learning Objectives

Acquire subject-specific theoretical and methodological knowledge.
Understand the possibilities and limitations of data analytics.
Are able to assess, compare and apply different methods of analysis.
Practice objective analysis of large amounts of data and decision-making.
Learn how to critically discuss completed tasks.
Acquire the ability to select and implement appropriate solution concepts and strategies to a given problem.

Study Programs

This course is mandatory for the following study programs.

MBA Digital Technologies
MBA Digital Transformation

This course is offered as an elective for the following study programs.

M.Sc. Applied AI
M.Sc. Cybersecurity
M.Sc. Advanced Digital Reality
M.Sc. Digital Leadership

Micro Degree

This course is offered as a micro degree.
German UDS Micro Degrees are compatible with the European MOOC Consortiums Common Micro Credentials Framework.
Micro Degrees will be rewarded with an equivalent of 5 ECTS.
Micro Degrees are offered to non-regular students and require a fee of €900.

Requirements

None

General Information

Teaching Format: Knowledge Essential
Total Workload Master: 125h (40h/85h) / 5 ECTS
Total Workload MBA: 100h (30h/70h) / 4 ECTS
Total Workload Micro Degree: 125h (40h/85h) / Equivalent to 5 ECTS
Module coordinator: Prof. Dr. Sonja Meyer
Examinations: Quizzes, presentation(s), essay(s)/paper(s), project report(s), written exam (tbd) - Details will be announced with course start.
Offered: Even quarters

Course Staff

Prof. Dr. Sonja Meyer

Sonja Meyer is a professor for Algorithmic Foundations of Digital Business Processes. Since 2018, she has taught foundational courses in algorithms, data structures, and theoretical computer science, along with advanced courses in software engineering for IoT and digitalization. Her research centers on modeling and automating sustainable, IoT-based business processes and developing sustainable IoT software solutions. Prior to her academic role, Sonja Meyer served as Research Manager for IoT projects at Bosch Software Innovations, where she led international projects in areas such as connected buildings and smart office solutions. She also worked as a Scientist at EMPA, conducting postdoctoral research on IoT and sustainability and leading projects to develop energy-efficient software applications. Sonja Meyer holds a PhD in Software Engineering from Université de Fribourg, Switzerland.

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