Data-intensive Systems


Content, progress and pedagogy of the module

Learning objectives


Students should achieve knowledge on the following topics in data-intensive systems:

  • concepts and techniques for analyzing large data volumes, such as data warehousing, On-Line Analytical Processing, and Data Mining
  • concepts and techniques for handling spatio-temporal data, including indexing and processing of queries
  • concepts and techniques for scalability for data-intensive systems, e.g., cloud computing

Topics will typically be exemplified by Internet-related application, such as web analytics, spatial web, and the like.

There will also be one or more optional subjects within data-intensive systems, including but not limited to:

  • concepts and techniques for managing web-related data such as XML, Semantic Web, and Web2.0 data
  • concepts and techniques for search engines


  • be able to explain concepts and techniques in data-intensive systems
  • be able to select and apply relevant concepts and techniques for a given problem in data-intensive systems


  • be able to apply concepts and techniques from data-intensive systems, including design and implementation of data-intensive systems.

Type of instruction

The teaching is organized according to the general teaching methods for the education, cf. chapter 3

Extent and expected workload

It is expected that the student uses 30 hours per ECTS, which for this activity means 150 hours



Name of examData-Intensive Systems
Type of exam
Written or oral exam
Assessment7-point grading scale
Type of gradingInternal examination
Criteria of assessmentThe criteria of assessment are stated in the Examination Policies and Procedures

Additional information

Contact: The Study board for Computer Science at or 9940 8854

Facts about the module

Danish titleDataintensive systemer
Module codeDSNSWFK102
Module typeCourse
Duration1 semester
Language of instructionDanish and English
Empty-place SchemeYes
Location of the lectureCampus Aalborg
Responsible for the module


Study BoardStudy Board of Computer Science
DepartmentDepartment of Computer Science
FacultyTechnical Faculty of IT and Design