DM837: Big Data (5 ECTS)

STADS: 15014501

Level
Master's level course

Teaching period
The course is offered in the spring semester.

Teacher responsible
Email: zhou@imada.sdu.dk

Timetable
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Comment:
Ubegrænset deltagerantal. 4. kvartal.

Prerequisites:
None

Academic preconditions:
The content of DM505 Database Design and Programming and DM532 Principles of Database Systems should be known. This course cannot be taken if DM822 Cloud Computing has already been or is currently taken.

Course introduction
The main purpose of this course is to give the participants an understanding of the technologies of Big Data analysis and management. It covers both traditional methods used in data warehouse and parallel database systems as well as modern technologies of cloud computing and massively parallel data analysis platforms.

Expected learning outcome

• Explain the techniques of data warehouse and parallel database systems
• Account for theories behind massively parallel data analysis systems
• Explain the design and trade-off 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 in the assignments in a clear and precise language, and in a structured fashion.

Subject overview
Data warehouse, parallel database systems, massively parallel data analysis, parallel data stream processing, Hadoop, MapReduce, GraphLab, Spark, Storm.

Literature

Meddeles ved kursets start.

Website
This course uses e-learn (blackboard).

Prerequisites for participating in the exam
Assignments. Pass/fail.

Assessment and marking:
Oral exam. External examiner, graded after Danish 7 mark scale (5 ECTS).

Expected working hours
The teaching method is based on three phase model.
Intro phase: 18 hours
Skills training phase: 8 hours

Educational activities Study phase: 12 hours

Language
This course is taught in English.

Course enrollment
See deadline of enrolment.

Tuition fees for single courses
See fees for single courses.