NDAK18001U Big Data Systems (BDS)

Volume 2024/2025
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.
Learning Outcome

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.
Literature

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.
Lectures, seminars and discussions.
  • Category
  • Hours
  • Lectures
  • 28
  • Preparation
  • 50
  • Project work
  • 127
  • Exam
  • 1
  • Total
  • 206
Oral
Collective
Credit
7,5 ECTS
Type of assessment
Written assignment
Oral examination, 20 minutes without preparation
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.

An overall grade will be given by taking both elements into account.
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 assesment

See Learning Outcome.