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[ 977PADCIADK22 ] KS (*)Introduction to Analytics and Digital Transformation
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(*) Leider ist diese Information in Deutsch nicht verfügbar.
Workload Ausbildungslevel Studienfachbereich VerantwortlicheR Semesterstunden Anbietende Uni
3 ECTS M1 - Master 1. Jahr Betriebswirtschaftslehre Markus Sinnl 2 SSt Johannes Kepler Universität Linz
Detailinformationen
Quellcurriculum Masterstudium Economic and Business Analytics 2023W
Ziele (*)Students understand how digital technologies can be employed to generate business value. They are able to analyze business processes and have basic knowledge on how they are supported by technology in current organizations. They know how data is processed and managed in current organizations and how to extract information relevant for business decisions. They are able to apply basic analytics techniques using appropriate tools to support business decisions.
Lehrinhalte (*)Basic ideas and techniques from descriptive, predictive, prescriptive and autonomous analytics; overview of the steps of the accompanying transformation process which is needed to allow a company to successfully apply these analytical techniques in practice; case studies, practical applications.
Beurteilungskriterien (*)Written exam, homework exercises
Lehrmethoden (*)The course content is taught using blended learning methods with interactive elements to consolidate knowledge.
Abhaltungssprache Englisch
Literatur (*)F. Provost, T. Fawcett: Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking, O'Reilly, current edition

T. H. Davenport, J. Harris: Competing on analytics - The new science of winning, Harvard Business Review Press, current edition

D. Bertimas, A. O’Hair, W. Pulleyblank: The Analytics Edge, Dynamic Ideas LLC, current edition

Other supplemental literature will be announced each semester.

Lehrinhalte wechselnd? Nein
Präsenzlehrveranstaltung
Teilungsziffer 100
Zuteilungsverfahren Zuteilung nach Vorrangzahl