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.
Lectures, seminars and discussions.
See Absalon when the course is set up.
The course builds on the knowledge acquired in the course
NDAK15006U Advanced Computer Systems (ACS).
Working knowledge of Java, including concurrency and communication mechanisms.
Notions of UNIX / shell scripting are helpful, but not required.
Academic qualifications equivalent to a BSc degree is recommended.
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 two parts:
a. Group project assignments with individual defense in the exam week;
b. Oral exam in the exam week.
The individual project assignment defense and oral exam should be carried out in one session and should last for 30 minutes in total (including grading, without preparation).
In the final grade, the weight of the different parts is as follows: oral exam 50%, group project with individual defense: 50%.
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Several internal examiners.
Criteria for exam assessment
See Learning Outcome.
Single subject courses (day)
- Project work
- Course number
- 7,5 ECTS
- Programme level
- Full Degree Master
- Study Board of Mathematics and Computer Science
- Department of Computer Science
- Faculty of Science
- Yongluan Zhou (4-89777e844f73783d7a843d737a)
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Courseinformation of students