Course Info
| Module [Module Number] | CM Data Analytics V [1277MBDMA1] |
| Regular Cycle | Winter Term |
| Teaching Form | Lecture and practice |
| Examination Form | Written test (90) |
| Teaching Language | English |
| ECTS | 6 |
| Instructor | Prof. Dr. Markus Weinmann |
| KLIPS 2.0 | Link |
Module Content
- Fundamentals of data storage, data cleansing and retrieval; data use and data quality for data analysis
- Fundamentals of metadata; methods of data integration; data models and software architectures for the integration of different data types
- Data management methods and practices (e.g. relational databases, SQL, NoSQL databases, data manipulation, access to data sources, Web APIs, scraping/crawling and parsing of text data)
- Basics of data visualization (e.g. cognition, design principles for diagrams and graphics, visualiza- tion of different data types)
- Methods and techniques of data visualization (e.g. tableau, R, dashboards, digital presentations)
Learning Objectives
Students …
- know and understand the relevant methods and theories for the points mentioned above under „Module content“.
- understand advanced, specialized theories / methods in the field of programming and data analytics.
- analyse current questions and challenges in the field of programming and data analytics.
- assess and discuss findings and research results of specialized theories / methods.
- act responsibly considering ecological, social and ethical criteria.
- develop work processes for real problems and challenges.