NDAK18001U Big Data Systems (BDS)
The goal of this course is to give the participants an
understanding of the technologies in computer systems for Big Data
analysis and management. It covers both traditional methods used in
data warehouses and parallel database systems, real-time
stream processing systems, transactional database systems, as well
as modern technologies of cloud computing and massively parallel
data analysis platforms.
The following main topics are contained in the course:
- Data warehouses;
- Parallel database systems;
- Massively parallel data analysis;
- Fast stream processing systems;
- Big graph processing;
- High-throughput transaction processing;
- Load balancing;
- Elastic scaling;
- Data partitioning.
- Techniques in data warehouses and parallel database systems.
- Techniques in data stream processing.
- Theories behind massively parallel data analysis systems.
- Design of and trade-offs in the modern systems introduced in the course.
- Develop programs and apply tools for big data management and analysis and deploy them on a cloud computing platform.
- Report work done with Big Data systems in a clear and precise language, and in a structured fashion.
- Design, implement, deploy and optimize Big Data systems.
- Analyze solutions in Big Data systems.
- Discuss research articles related to Big Data systems with colleagues.
- Plan and execute groups projects with Big Data systems and report the findings.
See Absalon when the course is set up.
Working knowledge of Java, including concurrency and communication mechanisms.
Notions of UNIX / shell scripting are helpful, but not required.
- Project work
PhD’s can register for MSc-course by following the same procedure as credit-students, see link above.
- 7,5 ECTS
- Type of assessment
- Continuous assessmentThe exam consists of four elements:
- seminar presentations of selected topics
- written reviews of research articles
- group project during the course
- oral exam in the examination week based on the project (20 minutes including grading, without preparation)
In the final grade the weight of the different parts is as follows: seminar presentation and review of research articles: 50%, group project and the oral exam: 50%.
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Several internal examiners.
Resubmission of (possibly revised) course elements; elements not redone are carried over with their original assessments. Project reports and article reviews must be resubmitted no later than two weeks before the re-exam date; seminar must be held no later than one week before the re-exam date; a new oral exam (if required) will be administered on the re-exam date itself.
Criteria for exam assesment
See Learning Outcome.