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Advanced Data Management for Data Analysis


Admission requirements

Not applicable.


The course will build on standard (relational) database concepts, techniques, algorithms, including Entity-Relationship model, Relational Data model, Relational algebra, SQL, transaction management, storage formats and access structures (indexes) as usually tough in bachelor's level database course. Familiarity with these is highly recommended for this course. Given that the course does not (only) aim at learning to use existing systems, but rather (also) at learning to build (parts of) data management and analysis systems, programming experience is system-oriented programming languages like C or C++ are also highly recommended.

Course objectives

The course will discuss advance data management techniques, algorithms data structures and systems to facilitate efficient and scalable analysis of large amounts of data ("Big Data"). Implementing selected parts / components of data management and analysis systems is part of the course.


The most recent timetable can be found on the students' website.

Mode of instruction

  • Lectures

  • Assignments / Implementation projects

  • Literature studies including presentations and discussions of selected literature

  • Reports

Total hours of study: 168 hrs. (= 6 EC)
Lectures: 26:00 hrs.
Practical work/assignments: 69:00 hrs.
Examination: 3:00 hrs.
Self-study: 70:00 hrs.

Assessment method

  • Written/oral exam

  • Homework assignments

  • (Research) project

The teacher will inform the students how the inspection of and follow-up discussion of the exams will take place.

Reading list

To be announced.


  • You have to sign up for courses and exams (including retakes) in uSis. Check this link for information about how to register for courses.


Lecturer: prof.dr. S. Manegold