Big Data Systems (BDS)
Course content
The goal of this course is to give the participants an
understanding of the technologies in computer systems for Big Data
management. It covers both traditional methods used in 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:
- Parallel database systems;
- Massively parallel data analysis;
- Fast stream processing systems;
- Distributed transaction processing;
- Fault-tolerance;
- Scalability;
- Event-based systems.
Knowledge of
- Theories and techniques in parallel database systems.
- Theories and techniques in data stream processing systems.
- Theories and techniques in distributed transactional systems.
- Design of and trade-offs in the modern systems introduced in the course.
Skills to
- 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.
Competences to
- Design, implement, deploy and optimise Big Data systems.
- Analyse 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 and C#, including concurrency and
communication mechanisms.
Notions of UNIX / shell scripting are helpful, but not required.
Academic qualifications equivalent to a BSc degree is
recommended.
As
a exchange, guest and credit student - click here!
Continuing Education - click here!
PhD’s can register for MSc-course by following the same procedure as credit-students, see link above.
- ECTS
- 7,5 ECTS
- Type of assessment
-
Written assignmentOral examination
- Type of assessment details
- The assessment is based on the following two elements:
1. Group project assignments (3-5) with individual defence in the exam week;
2. Oral examination in the exam week.
The individual project assignments defence 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:
1. Group project with individual defence: 50%.
2. Oral examination: 50% - Aid
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Several internal examiners.
- Re-exam
-
Same as the ordinary exam
The oral examination and project assignments defense will take place on the re-exam date.
Resubmission of project assignments no later than three weeks before the re-exam date. Project assignments not redone will be transferred with the original assessments.
Criteria for exam assessment
See Learning Outcome.
Single subject courses (day)
- Category
- Hours
- Lectures
- 28
- Preparation
- 50
- Project work
- 127
- Exam
- 1
- English
- 206
Kursusinformation
- Language
- English
- Course number
- NDAK18001U
- ECTS
- 7,5 ECTS
- Programme level
- Full Degree Master
- Duration
-
1 block
- Placement
- Block 2
- Schedulegroup
-
C
- Capacity
- 50
The number of seats may be reduced in the late registration period - Studyboard
- Study Board of Mathematics and Computer Science
Contracting department
- Department of Computer Science
Contracting faculty
- Faculty of Science
Course Coordinator
- Yongluan Zhou (4-7d6b727843676c316e7831676e)
Teacher
Yongluan Zhou
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