Advanced Data Mining Techniques, Databases and Big Data (from WS 20/21)
Advanced Data Mining Techniques, Databases and Big Data
|State of the module||Compulsory module|
|Hours of compulsory in credit hours||4|
|Learning outcome/ competencies|
Students are able to explain and name the advantages and drawbacks of processes for storing and processing extremely large and unstructured quantities of data. They are familiar with modern database technology and can describe the differences to conventional rational databases. Students can define terms and processes such as ETL, data warehouse, data mart, OLAP and Hadoop as they relate to data manage-ment in distributed databases, in streams, in collections for complex structures or for spatially and temporally mobile objects.
|Method of examination|
(applicable are §§ 9-14 RStPO)