[ 921CGELCDMK13 ] KV Conceptual Data Modeling

Workload Education level Study areas Responsible person Hours per week Coordinating university
3 ECTS M1 - Master's programme 1. year Computer Science Wolfram Wöß 2 hpw Johannes Kepler University Linz
Detailed information
Original study plan Master's programme Computer Science 2022W
Objectives Data modeling is essential to assure high data quality, which is an important prerequisite for industry, data-driven decisions, or artificial intelligence. It is an important skill for data scientists or others involved with data analysis. This course aims at a theoretical and practical basis on data modeling. The process of data modeling is demonstrated by means of real-world case studies and examples. Practical experience is gained by using the methods and applying them in exercises and examples.
Subject Introduction to data modeling, Data model quality, The Entity-Relationship-Model (ER-Model), Transformation of an ER-Model into a Relational Model, Extensions of the ER-Model, Semantic data models

Conceptual Data Modeling enables students

  • to obtain a theoretical foundation in conceptual data modeling
  • to gain knowledge about relevant models and methods and to apply them in real-world projects
  • to transform a conceptual data model into a specific database schema
  • to gain practical experiences by applying the methods in exercises and examples
Criteria for evaluation Exam as well as the submission and evaluation of exercises
Methods Slide-based presentation, exercises
Language English
Study material Will be announced at the start of the semester
Changing subject? No
Corresponding lecture INMAWKVKDMO: KV Konzeptionelle Datenmodellierung (3 ECTS)
On-site course
Maximum number of participants -
Assignment procedure Direct assignment