Professur für Service Analytics

Business Analytics

Vorlesung mit Übung für Bachelorstudierende

Prof. Dr. Catherine Cleophas (Vorlesung)
Peyman Kazemi (Übung)

 

Zusammenfassung:

Business Analytics considers the objective of supporting business decisions based on quantitative data. The topic is closely connected to information systems engineering, as business analytics relies on data models and algorithms to make predictions and suggest solutions. At the same time, business analytics requires domain expertise in relevant topics of business and economics to generate relevant and applicable approaches and to successfully communicate findings.The lecture will introduce relevant theoretical concepts connected to business analytics and decision support. In computer-based exercise sessions, the students can implement basic business analytics solutions in software packages such as MS Office.
 

Inhalt:

The course will cover basic topics of Business Analytics, such as:
  • Introduction to Business Analytics
  • Business Information Systems
  • Process Modelling
  • Problem Structuring Methods / “Soft Operations Research”
  • Principles of Information Systems Engineering
  • Project Management for Analytics Projects
  • Spreadsheet Analytics
  • Algorithm Basics
  • Data, Data Models, Information, and Knowledge
  • Introduction to Data Mining
  • Introduction to Web Scraping
  • Introduction to Simulation Modelling
  • Communicating Findings
     

Lernziele:

Participants gain theoretical background knowledge in the following areas:
  • Process and problem modelling
  • Information systems engineering
  • Data models and data mining
  • Algorithms and simulation modelling

They also gain hands-on experience in applying these concepts via widely used software, e.g., MS Office.
 

Literatur:

  • Laudon & Laudon, Management Information Systems: Managing the digital firm.C
  • Guerrero, Excel Data Analysis
  • Pidd, Tools for thinking
  • Further literature is announced during the module

 

Weitere Informationen:

 

Semesterspezifische Informationen, Ort und Zeit der Veranstaltungen sowie die Prüfungen werden im UnivIS sowie in OpenOLAT bekannt gegeben.