Advanced Data Mining Techniques, Databases and Big Data

Advanced Data Mining Techniques, Databases and Big Data

Duration1 semester
State of the moduleCompulsory module
Hours of compulsory in credit hours6
Learning outcome/ competencies

This module builds upon the extensive knowledge base you have developed over your studies, with specific reference to the use of data analysis techniques. The module will give you enhanced insight into the methods of storing and processing very large, and—above all, unstructured data sets.

Initially you will examine database technologies as they are deployed in the storage of data sets. Particular attention will be paid to the design and management aspect of databases. Additionally, you will examine contemporary frameworks such as ETL, OLAP and Hadoop, and discuss how they operate with regard to the storage of data sets in distributed databases, streams and collections of complex structures or for objects-in-motion in space and time.

After a comprehensive survey of data storage options, you will gain insight into the innovative techniques for data analysis, and—in particular—the analysis of unstructured data sets. This includes text and web mining, image mining and social-network analysis.

You will apply the knowledge gained in this module to practical exercises in the laboratory using software tools. Here, you will be confronted with real-world scenarios from the domains of business, science and medicine.

Necessary requirementsNone
Recommended requirements
  • MPMD 2.2 Advanced Computational Data Analytics
Method of examination
(applicable are §§ 9-14 RStPO)   

Written Examination (120 minutes) and (2 Assignments):

  • Written Examination 65 %
  • Assignments 35 %