6 ECTS credits
172 h study time

Offer 2 with catalog number 4011474FNR for all students in the 1st semester at a (F) Master - specialised level.

Semester
1st semester
Enrollment based on exam contract
Impossible
Grading method
Grading (scale from 0 to 20)
Can retake in second session
Yes
Taught in
English
Faculty
Faculty of Sciences and Bioengineering Sciences
Department
Computer Science
Educational team
Bas Ketsman (course titular)
Activities and contact hours
26 contact hours Lecture
26 contact hours Seminar, Exercises or Practicals
120 contact hours Independent or External Form of Study
Course Content

In the course Scalable Data Management Systems, we study specialized systems and algorithms developed to support data-intensive applications at scale. The course takes a principled approach and covers aspects from parallel and distributed databases, MapReduce derivatives, and other relevant systems. Course topics include data partitioning, distributed query planning, and scalable transaction management.

Course material
Digital course material (Required) : Voor specifieke cursusonderwerpen, zullen tevens verwijzingen naar relevant aanvullend materiaal (onderzoeksartikelen, boeken en hoofdstukken van boeken, websites, tutorials, enz.) verstrekt worden.
Additional info

The course material consists of slides and a number of scientific articles.
These will be made available on the learning platform.

Learning Outcomes

General competencies

By the end of the course, the student will be able to:

  • Explain and relate to each other the main principles, techniques and trade-offs underlying scalable data management systems.
  • Name current state-of-the-art systems as well as approaches in academia and be able to place them within the domain of scalable data management systems.
  • Analyse the trade-offs of different approaches to data management in terms of efficiency, scalability, latency, …
  • Choose and motivate the most appropriate existing system architecture and technology for a certain task.
  • Link system architectures to appropriate formal frameworks and cost models
  • Design and motivate data layouts and query plans suitable for a system architecture, the needs of an application, and specific workloads.
  • Understand and critically analyse research papers within the field and answer questions about the contents of those papers.
  • Independently continue the study of systems, techniques, and new progress in the field of scalable data management systems.

Grading

The final grade is composed based on the following categories:
Written Exam determines 60% of the final mark.
PRAC Practical Assignment determines 40% of the final mark.

Within the Written Exam category, the following assignments need to be completed:

  • Written exam with a relative weight of 1 which comprises 60% of the final mark.

    Note: During the exam period a written exam covering all the course topics will be conducted.

Within the PRAC Practical Assignment category, the following assignments need to be completed:

  • Project with a relative weight of 1 which comprises 40% of the final mark.

    Note: During the semester students have to work on a project in groups.

Additional info regarding evaluation

The final grade is a weighted average. During the semester an assignment has to be done (counts for 40% of the final grade). During the exam period a written exam covering all the course topics will be conducted as well as a discussion of the assigned project (counts for 60% of the final grade). In order to pass the course, the final grade has to be at least 10/20. Furthermore, each individual grade (assignment or written exam) has to be at least 8/20, otherwise the lower of these two grades becomes the final grade.

In case of an overall failure, partial marks for the assignment, if the student obtains at least 10/20 for the assignment, are transferred to the second session. Partial marks for the written exam, if the student obtains at least 10/20 for the written exam, are transferred to the second session. Students may not relinquish partial marks.

In the second exam period, assignments that were not satisfactory can be reworked and defended again. The written exam can be redone if the student failed in first session. The final mark is calculated in the same way as in the first exam period.

Allowed unsatisfactory mark
The supplementary Teaching and Examination Regulations of your faculty stipulate whether an allowed unsatisfactory mark for this programme unit is permitted.

Academic context

This offer is part of the following study plans:
Master in Applied Sciences and Engineering: Applied Computer Science: Standaard traject
Master of Applied Sciences and Engineering: Computer Science: Artificial Intelligence
Master of Applied Sciences and Engineering: Computer Science: Multimedia
Master of Applied Sciences and Engineering: Computer Science: Software Languages and Software Engineering
Master of Applied Sciences and Engineering: Computer Science: Data Management and Analytics
Master of Applied Informatics: Profile profiel Big Data Technology
Master of Applied Informatics: Profile profiel Artificial Intelligence