Data & Information Management

Department
  • Master's Program Management, Communication & IT
Course unit code
  • MCI-M-1-DIM-DIM-ILV
Level of course unit
  • Master
Semester when the course unit is delivered
  • 1
Number of ECTS credits allocated
  • 5.0
Name of lecturer(s)
  • FH-Prof. Dr. Schöttle Pascal
  • FH-Prof. Dr. Bernsteiner Reinhard
  • Endres Julian, BSc MA
Learning outcomes of the course unit
  • Students know the definitions of central terms and concepts from the field of data and information management. They can distinguish between types of data and explain their meaning. They have an overview of typical data models and can identify corresponding database systems. They will be able to apply the typical processes and frameworks. They know the most important technologies and can describe their areas of application.
Mode of delivery
  • face-to-face
Prerequisites and co-requisites
  • none
Course contents
  • - Definitions of central terms and concepts (for example Big Data, Small Data, Open Data...)
    - Different types of data and their use
    - Typical data structures and corresponding database systems (relational or non-relational)
    - Typical data and information management processes and frameworks
    - Data and information security
    - Central standards and regulations in the area of information security management
    - New developments and influences on data and information management
    - Central technologies on application level (e.g. cloud computing, data fabric/factory, visualization, ontologies)
Recommended or required reading
  • - Marr, B. (2017). Data strategy: How to profit from a world of big data, analytics and the internet of things. London, New York: Kogan Page: Kogan Page.
    - Henderson, D., & Earley, S. (Eds.) (2017). Dama-DMBOK: Data management body of knowledge (Second edition). Basking Ridge, New Jersey: Technics Publications: Technics Publications.
    - Schwirn, M. (2021). Small data, big disruptions: How to spot signals of change and manage uncertainty. Newburyport MA: Career Press: Career Press.
    - Jackson, P., & Carruthers, C. (2019). Data-driven business transformation: How businesses can disrupt, innovate, and stay ahead of the competition. Chichester West Sussex United Kingdom: John Wiley & Sons: John Wiley & Sons.
    - Strengholt, P. (2020). Data management at scale: Best practices for enterprise architecture (First edition). Sebastopol CA: O'Reilly Media: O'Reilly Media.
Planned learning activities and teaching methods
  • The course comprises an interactive mix of lectures, discussions and individual and group work.
Assessment methods and criteria
  • To monitor the students’ learning this course will provide ongoing assignments as a basis for feedback and grading (formative assessment) and/or will evaluate the students learning at the end of the course or an instructional unit via exams, final project reports, essays or seminar papers (summative assessment).
Language of instruction
  • English
    • AACSB/FIBAA