Data & Analytics 1: Data Engineering
Niveau
Bachelor
Learning outcomes of the courses/module
The students
- understand what database systems are used for and how they work
- know different database systems and can compare them with each other
- have a detailed understanding of relational database systems
- can develop and implement data structures for a problem
- can independently represent real-world situations as a data model
- can transfer data models into a relational data structure
- can apply database systems in practice
- can interact with database systems
- can carry out basic database management activities with NoSQL systems
Prerequisites for the course
none
Course content
- Basics of database systems and data management
- Data modeling (single entity, attributes, cardinality, conditionality, relationship types)
- Key candidates, super keys, and primary keys
- Normalization of data structures (at least 1, 2, 3)
- Interaction with relational databases with the support of SQL in the areas of DDL, DML, and DQL
- Basic database management activities on advanced database concepts in the area of NoSQL
Recommended specialist literature
- Watson, Richard T.: Data Management. Databases and Organizations. 6th edition, eGreen Press, 2013
- Date, Chris: SQL and Relational Theory. 3rd edition, O'Reilly Media, 2015
- Kaufmann, Michael; Meier, Andreas: SQL & NoSQL Datenbanken. 9th edition. Springer Vieweg, 2022
Assessment methods and criteria
Portfolio review
Language
German
Number of ECTS credits awarded
6
Share of e-learning in %
20
Semester hours per week
3.0
Planned teaching and learning method
Presentations, group work, project work, individual tasks, presentations and discussions
Semester/trimester in which the course/module is offered
1
Name of lecturer
STGL
Academic year
1
Key figure of the course/module
DAT1
Type of course/module
integrated lecture
Type of course
Compulsory
Internship(s)
no