Corporate Transformation Management PT
Apply Icon
Apply
now

Data Analytics & Business Modeling

level of course unit

2.Semester Master: 1st Study cycle

Learning outcomes of course unit

The students:
• understand the potential, but also the challenges of Big Data for business modeling
• can apply selected statistical and quantitative methods for business modeling
• can interpret results from data analytics and use them for business modeling
• can set up business analytics reporting

prerequisites and co-requisites

2. Semester: no information

course contents

Fundamentals:
• 4 development stages of business analytics (descriptive analytics, diagnostic analytics, predictive analytics, prescrip-tive analytics)
• Change of control processes (reactive-analytical vs. proactive-forecasting; agile, real-time and based on data analy-sis; fact-based, differentiated and fast; cross-company and cross-value-added)
• Changing business modeling framework (highly trained specialists; changing roles, organizations, and profiles; infor-mation processes and quality of decisions; use of internal and external data; consistent governance)

Analysis methods:
• Structural testing analysis methods (regression analysis [linear, non-linear, logistic, exponential, etc.], time series analysis, variance/covariance analysis, discriminant analysis, contingency analysis, structural equation analysis, con-joint analyses)
• Structural discovery analysis methods (factor analysis, cluster analysis, neural networks, multidimensional scaling, correspondence analysis, data envelopment analysis)

Business Analytics Process:
• Problem identification (identification of the need for action, delineation of issues, formulation of tasks)
• Exploration (data acquisition, data mining)
• Optimization (determination of implementation hurdles and costs, planning and budgeting, development of optimiza-tion concept)
• Monitoring (monitoring effectiveness, setting up a monitoring system, defining key performance indicators)

recommended or required reading

Becker, W., Ulrich, P. & Botzkowski, T. (2016) Data Analytics im Mittelstand, Wiesbaden.
Dorschel, J., Hrsg. (2015) Praxishandbuch Big Data: Wirtschaft - Recht - Technik, Wiesbaden.
Knauer, D. (2015) Act Big - Neue Ansätze für das Informationsmanagement: Informationsstrategie im Zeitalter von Big Data und digitaler Transformation, Wiesbaden.
Jahn, M. (2017) Industrie 4.0 konkret: Ein Wegweiser in die Praxis, Wiesbaden.

assessment methods and criteria

Module exam (Data Analytics & Business Modeling, Risk Management & Monitoring, Forecasting Methods & Scenario Techniques, Mergers & Acquisitions)

language of instruction

German

number of ECTS credits allocated

2.5

eLearning quota in percent

0

course-hours-per-week (chw)

2

planned learning activities and teaching methods

• The course, which is mostly dialog-oriented, usually consists of the triad of practical relevance, academic structuring, and the independent development of integrative case studies from immediate professional and consulting practice.

semester/trimester when the course unit is delivered

2

name of lecturer(s)

Director of studies

year of study

1

recommended optional program components

none

course unit code

3

type of course unit

integrated lecture

mode of delivery

Compulsory

work placement(s)

none

Contact

Situm Mario
Prof. (FH) DDr. Mario Situm, MBA
Director of Studies
+43 5372 71819 147
Mario.Situmfh-kufstein.ac.at
questions? Any
Any questions?
We are here to help you.
+43 5372 71819 500
bewerbungfh-kufstein.ac.at
Infofolder
Infofolder

Internationales Symposium Restrukturierung

Am 22. Oktober 2021 findet das „10. Internationale Symposium Restrukturierung“ an der Fachhochschule Kufstein Tirol statt.

Im Mittelpunkt der Jubiläumsveranstaltung steht das Rahmenthema Wie geht´s weiter?.

Restrukturierungs- und Turnaround-Management

Praktiker:innenhandbuch: 
Restrukturierungs- und Turnaround-Management, 2. Auflage, Exler (Hrsg.)

Mehr Infos:
Publikationen

Restrukturierungs-Qualitätssiegel für Kufsteiner Masterstudiengang

Der berufsbegleitende Masterstudiengang Unternehmensrestrukturierung & -sanierung ist nach einjähriger Begutachtung offiziell TMA-zertifiziert – das renommierte Qualitätssiegel des Verbandes der deutschen Restrukturierungsexperten (TMA).

Weitere Informationen