Jedes Modul umfasst 3 ECTS. Sie wählen insgesamt 10 Module/30 ECTS in den folgenden Modulkategorien:
- 12-15 ECTS in Technisch-wissenschaftlichen Modulen (TSM)
TSM-Module vermitteln Ihnen profilspezifische Fachkompetenz und ergänzen die dezentralen Vertiefungsmodule. - 9-12 ECTS in Erweiterten theoretischen Grundlagen (FTP)
FTP-Module behandeln theoretische Grundlagen wie die höhere Mathematik, Physik, Informationstheorie, Chemie usw. Sie erweitern Ihre abstrakte, wissenschaftliche Tiefe und tragen dazu bei, den für die Innovation wichtigen Bogen zwischen Abstraktion und Anwendung spannen zu können. - 6-9 ECTS in Kontextmodulen (CM)
CM-Module vermitteln Ihnen Zusatzkompetenzen aus Bereichen wie Technologiemanagement, Betriebswirtschaft, Kommunikation, Projektmanagement, Patentrecht, Vertragsrecht usw.
In der Modulbeschreibung (siehe: Herunterladen der vollständigen Modulbeschreibung) finden Sie die kompletten Sprachangaben je Modul, unterteilt in die folgenden Kategorien:
- Unterricht
- Dokumentation
- Prüfung
Business Analytics (BA) is the science of analyzing enterprise data with statistical methods. The aim is to better understand market, customers, internal processes and the competitive environment, allowing for better and more informed decisions in business. As such, BA goes well beyond simply presenting data, numbers and tables, but focuses on finding new patterns, explaining the occurrence of results and forecasting future development. The essence is to find meaning in the data und successfully deploy it into the daily business life. This course will provide an overview over the principal questions, practices, methods, tools and goals in BA.
Eintrittskompetenzen
Basic knowledge in statistics on the level of an introductory stochastics course.
Lernziele
The students understand the benefits that BA offers for an enterprise, i.e. they perceive the potential that quantitative analysis of business data harbors and that it is important to turn data into information. They acquire a comprehensive overview how and in which fields BA can offer added value to a company. The students are able to perform basic tasks in e.g. customer selection, segmentation, demand forecasting and maintenance planning on their own means. They recognize points of contact to other, technical modules such as Predictive Modelling and can strengthen their skills in statistical data analysis.
Modulinhalt
Throughout the course, there will be a strong focus on the process of gaining information from and making use of business data. That involves setting realistic goals, selecting suitable data, drawing unbiased conclusions, reporting facts correctly and deploying the results. This goes along with pointing out some common misconceptions and pitfalls that often repeat themselves in statistical analysis.
The meat of the course will be made up by case studies that cover BA tasks such as customer segmentation, churn analysis, customer selection, demand forecasting, point-of-sale data, customer lifetime value, dynamic pricing, planned maintenance, service science, et cetera. The use and benefits of each of these topics will be explained, methods for practically solving the analysis tasks will be presented in an accessible, non-technical manner and focus on the validity and generalizability of the results will be laid.
Lehr- und Lernmethoden
Lectures and practical work on computer with suitable BA tools.
Bibliografie
Slides and lecture notes will be available in addition to recommended book chapters.
Vollständige Modulbeschreibung herunterladen
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