Advanced Topics in Databases
Course Organization
| Lecturer: | Gunter Saake Eike Schallehn Veit Köppen |
| SWS: | 2 + 2 |
| Target audience: | Master IF, WIF, IIF, CV, DKE |
| Time/place (Lecture): | Wednesday 11:15, 05/211 |
| Time/place (Exercise): | Monday 13:15, 05/209; Thursday 11:15, 05/208 (Starting April 23) |
Contents
In the lecture students will be made familiar with most recent technological developments in data management. The first goal is to enable the attendees to use these new technologies in their professional careers in industry. Furthermore, the lecture focuses on aspects currently addressed in scientific research being on the verge to wide usage in current applications, and this way, enabling students to participate in academic and industrial research.Topics of the lecture will frequently change in accordance with current research directions in the database community and represent cutting-edge aspects as for instance
- Indexing and storage techniques for new applications and data types,
- Data management for embedded devices and sensor networks,
- Self-management capabilities of database management systems
- Column-oriented DBMS
- etc.
Lecture
Slides/handouts four the lecture will be made available here during the running lecture.- Introduction slides (pdf)
- Cloud Data Management slides (pdf)
- Multimedia Retrieval - Indexing and Storage Techniques slides (pdf)
Prerequisites
A Database introduction course (like Databases I or Data Management at the University in Magdeburg) are a necessary prerequisite. Background knowledge about internal database operations (query processing, storage structures, distributed data management, etc.) is advantageous.Exercise
Exercise assignments will be published here throughout the course of the lecture.- Exercises begin at Monday 23rd of April. New: 2nd exercise Thursdays at 11:15.
- Exercise 1: Cloud storage, applications in the cloud, key value stores
- Exercise 2: Cloud computing, MapReduce, and architectures
- Exercise 3: Cloud and SQL, query languages for the cloud
- Exercise 4: Multimedia, retrieval, and data handling
- Exercise 5: Vector space model, distance (vector), dimensionality
