Big Data (DLMBBD)

Module Title: Big Data

Module No.:


Semester / Term:



Minimum 1 Semester

Module Type(s):


Regularly offered in:


Workload: 300 h

Credit Points: 10

Admission Requirements:


Language of Instruction:


Contributing Courses to Module:


Self-study: 200 h
Self-examination: 50 h
Tutorials: 50 h

Course Coordinator(s) / Tutor(s):

Please see the current list of tutors on the Learning Management System.

Module Director:

Prof. Dr. Markus C. Hemmer

References to Other Programs:

  • Master of Business Administration

References to Other Modules in the Program:

  • Corporate Finance

Qualification and Educational Objectives of the Module:

Data Utilization:
Upon successful completion, students are able

  • to understand how identity, similarity and diversity of data can be utilized in problem-solving approaches.
  • to differentiate between complicated and complex systems of investigation.
  • to identify the variability of a problem under investigation.
  • to differentiate between invariant and dynamic features of an investigated system.
  • to synthesize the gained insights to propose a reliable data analytics solution.

Application Scenarios and Case Studies:
Upon successful completion, students are able

  • to establish an application scenario for data science within a self-organized team.
  • to identify requirements and appropriate technologies for data collection.
  • to evaluate and select applicable technologies for data pre-processing and processing.
  • to assess challenges and risks of the selected approach.
  • to clearly define the outcome and value of the approach.
  • to elaborate a conceptual design document and a presentation for decision-makers.

Course Content of the Module:

Data Utilization

  • Pattern Recognition
  • Natural Language Processing
  • Image Recognition
  • Detection and Sensing
  • Problem Solving
  • Decision-making

Application Scenarios and Case Studies:

  • Workflow overview
  • Fields of application
  • Sprint Planning; Sprint
  • Sprint Retrospective
  • Committee Presentation

Teaching Methods:

See the contributing course outlines


See the contributing course outlines

Percentage of the Module Grade Relative to the Final Grade for the Program:


Prerequisites to Qualify for Assessment:


See the contributing course outlines

Exam, 90 min. (50 %)
Written Assessment: Case Study (50 %)