Data modelling and storage
Niveau
2nd Study cycle, Master
Learning outcomes of the courses/module
The following learning outcomes are developed in the course:
- Students know the central concepts of data modelling.
- Students can independently develop data models for a given scenario.
- Students know different solutions for data storage.
- Students can compare different storage solutions with regard to their suitability for a given scenario.
- Students know the central concepts of data modelling.
- Students can independently develop data models for a given scenario.
- Students know different solutions for data storage.
- Students can compare different storage solutions with regard to their suitability for a given scenario.
Prerequisites for the course
none
Course content
The following content is discussed in the course:
- Data modelling for relational data structures
- Database interaction in SQL (DDL, DML, DQL)
- Non-relational data storage concepts (NoSQL databases)
- Implementing data structures
- Integrating data structures into applications
- Data modelling for relational data structures
- Database interaction in SQL (DDL, DML, DQL)
- Non-relational data storage concepts (NoSQL databases)
- Implementing data structures
- Integrating data structures into applications
Recommended specialist literature
PRIMARY LITERATURE: - Kleppmann, M. (2017): Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scala-ble, and Maintainable Systems (Ed. 1), O'Reilly Media, Farnham (ISBN: 978-1449373320)
SECONDARY LITERATURE: - Celko, J. (2013): Joe Celko's Complete Guide to NoSQL: What Every SQL Professional Needs to Know about Non-Relational Databases (Ed. 1), Morgan Kaufmann, Waltham (ISBN: 978-0124071926)
SECONDARY LITERATURE: - Celko, J. (2013): Joe Celko's Complete Guide to NoSQL: What Every SQL Professional Needs to Know about Non-Relational Databases (Ed. 1), Morgan Kaufmann, Waltham (ISBN: 978-0124071926)
Assessment methods and criteria
Written exam
Language
German
Number of ECTS credits awarded
6
Share of e-learning in %
17
Semester hours per week
3.0
Planned teaching and learning method
English version available soon
Semester/trimester in which the course/module is offered
1
Name of lecturer
Prof. (FH) Dr. Michael Kohlegger, Prof. (FH) PD Dr. Mario Döller
Academic year
1
Key figure of the course/module
DTS.1
Type of course/module
integrated lecture
Type of course
Compulsory