| Detailinformationen |
| Quellcurriculum |
Masterstudium Computer Science 2022W |
| Ziele |
(*)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.
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| Lehrinhalte |
(*)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
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| Beurteilungskriterien |
(*)Exam as well as the submission and evaluation of exercises
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| Lehrmethoden |
(*)Slide-based presentation, exercises
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| Abhaltungssprache |
Englisch |
| Literatur |
(*)Will be announced at the start of the semester
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| Lehrinhalte wechselnd? |
Nein |
| Äquivalenzen |
(*)INMAWKVKDMO: KV Konzeptionelle Datenmodellierung (3 ECTS)
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