Students:

• recognize database systems and identify the differences;
• design, analyze and model databases;
• understand the principles of normalization and are able to identify redundancies;
• understand the principles of SQL and to create data evaluations.

none

The course will cover the following topics/content:

• Selected database systems
• Methods and modeling of database design (ERM diagrams, normalization, redundancy detection and avoidance)
• Extracting or importing data from databases using query languages (SQL)

Edlich, S. (2011): NoSQL. Einstieg in die Welt nichtrelationaler Web 2.0 Datenbanken. 2. aktualisierte und erweiterte Auflage. München: Hanser.
Freiknecht, J./Papp, S. (2018): Big Data in der Praxis. Lösungen mit Hadoop, Spark, HBase und Hive. Daten speichern, aufbereiten, visualisieren. 2. erweiterte Auflage. München: Hanser.
Kudraß, T./Brinkhoff, T. (2015): Taschenbuch Datenbanken. 2. neu bearbeitete Auflage. München: Hanser.
Schels, I. (2019): Business Intelligence mit Excel. Datenanalyse und Reporting mit PowerQuery, PowerPivot und Power BI Desktop; Für Excel 2010 bis 2019. München: Hanser.
Seminar documentation publisher Helmut Dettmer: Database Administration. Training material for Access 2016 introduction. Ed. by Seminarunterlagen-Verlag Helmut Dettmer. Available online at www.Dettmer-verlag.de

Moderated group work, lecture, discussion, case work, project

Cumulative module examination
The module grade is calculated weighted by the ECTS credits of the individual courses (ILV - integrated lecture) of the module and results as follows:
ILV "Data Management" - 3 ECTS
Assessment type: Continuous assessment
Assessment method/s: group work, written final exam