Entry requirements

Admitted to the Master's Programme in Management, Communication and IT, and 15 credits from semester 1.

Learning outcomes

In terms of knowledge and understanding, after completed course the student should be able to:

• describe key concepts, applications and technical terms in the area of decision support systems,
• describe how decisions are made in an organisational context and what control systems this requires,
• describe different types of data as well as data sources and their characteristics,
• describe relationships between data, knowledge, systems, and business value,
• explain application areas for decision support systems in an organisational context.

In terms of skills and abilities, after completed course the student should be able to:

• analyse organisational problems and propose solutions in the form of decision support systems,
• use tools to analyse and visualize data,
• conduct an independent, smaller study in the area, including identifying a relevant question and problem area, choosing the appropriate research methods, and defending the study in a seminar.

In terms of judgement and approach, after completed course the student should be able to:

• evaluate decision support systems in terms of suitability for different types of data;
• evaluate advantages and disadvantages related to the implementation of decision support systems,
• identify and critically discuss ethical issues in relation to decision support systems.

Content

The course introduces the student to how information systems can support decision-making in modern business environments. The course focuses on decision support and decision support systems, an area often called analytics, i.e., how different technologies and systems can be used to support descriptive, predictive, and prescriptive applications in the field. Areas covered include data warehousing, data science, data and text mining, expert systems and artificial intelligence. During the course, the student will practice conducting and interpreting various analyses using decision-support techniques, e.g., data mining tools. The course also deals with decision-making and decision-making processes from a theoretical point of view, to provide the student with the tools needed to identify system needs, plan system implementation, and anticipate advantages and disadvantages of implementation. During the course, the student will carry out a small study in the area. Finally, ethical and societal problems arising from the implementation of decision support systems are also discussed.

Instruction

Lectures, labs, and seminars.

Assessment

Written exam, assignments, labs, and seminars.

If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the University's disability coordinator or a decision by the department's working group for study matters.