1.1 Objectives, as Specified in the Higher Education Act (1992:1434), Chapter 1, 9 §:
Second-cycle courses and study programmes shall be based fundamentally on the knowledge acquired by students during first-cycle courses and study programmes, or its equivalent.
Second-cycle courses and study programmes shall involve the acquisition of specialist knowledge, competence and skills in relation to first-cycle courses and study programmes, and in addition to the requirements for first-cycle courses and study programmes shall:
- further develop the ability of students to integrate and make autonomous use of their knowledge
- develop the students‘ ability to deal with complex phenomena, issues and situations, and
- develop the students‘ potential for professional activities that demand considerable autonomy, or for research and development work.
Knowledge and understanding
For the degree of Master the student must
- demonstrate knowledge and understanding in the main subject area, including both an overview of the area and deeper knowledge of certain parts of the area as well as insight into current research and development in the area, and
- demonstrate advanced methodological awareness in the main subject area of the programme.
Skills and ability
For the degree of Master the student must
-demonstrate an ability to integrate knowledge and to analyse, judge and handle complex phenomena, issues and situations even with limited information,
- demonstrate an ability to independently identify and formulate issues and to plan and carry out, using suitable methods, demanding tasks within the given timeframe,
- demonstrate an ability to, both orally and in writing, present and discuss conclusions and the knowledge and arguments on which these are based in dialogue with different groups, and
- demonstrate the skill required to take part in research and development work or to work in other demanding activities.
Critical skills and approach
For the degree of Master the student must
- within the main subject area demonstrate an ability to make judgements with reference to relevant scientific, social and ethical criteria and demonstrate awareness of ethical aspects of research and development work,
- demonstrate insight into the possibilities and limitations of science and its role in society and the responsibility of individuals in how it is used, and
- demonstrate the ability to identify his or her own need of further knowledge and to take responsibility for the development of his or her own knowledge.
On completion of the programme, students shall be able to:
- Use and implement robust analytical models in organizations within a given time frame.
- Manage large amounts of data in an organisation so as to be able to integrate and incorporate business intelligence into day to day decision making.
- Apply specialised theoretical and practical knowledge to be able to critically analyse, evaluate, synthesise and model data.
- Communicate methods, results, and knowledge using appropriate techniques to both specialists and laymen within an organization.
- Critically analyze and evaluate the relevant tools that an organization uses to better understand their business and to improve decision making.
- Review and reflect on the social and ethical issues, norms and relationships and act to ensure and execute them. Proper care must be ensured while handling sensitive and confidential data. Typical examples include information about bank customers, credit card information, and patient information.
The BI Program gives an intensive and broad training in information analysis, information modelling, decision making – key components in the BI chain training system - which integrate the core components from AI with in analytical skills in Information Systems with Statistics principles. This design aims for students to meet increasing global challenges in careers and provide the students with competence and capability from advanced data analysis research to enterprise management skills.
The one year master programme in business intelligence consists of four periods. During each of these, the students are taking two courses in parallel. During the program knowledge and skills in the area Micro Data Analysis and Big Data analysis is given. First semester during period 1 and 2 students are taking courses in Business Intelligence and Artificial Intelligence. In parallel they first take the course Statistical computing with R and later the course Data collection and data quality. During the semester the students are trained in analysis of company data both with statistical methods and methods coming from computer science in a Business Intelligence context. Furthermore, it addresses issues relating to data collection and data quality. At the end of the program, students have had courses related to different types of BI technologies which can be used in organizations. The program consists of courses that train students in practical skills to collect, store and analyze data.
During the second semester the students deepen their knowledge in data analysis with the help of the courses Datamining and Spatial analysis and GIS. During this semester the students write their Master thesis. The semester starts with a course in datamining and spatial data analysis. In the beginning of this semester, students will formulate a basic outline of their thesis work i.e. problem definition, hypothesis and a list of references. The students also have to describe how they intend to solve the problem and explain what material that will be used in the thesis and how they plan to access it. The plan should also include what need of new learning learning that exist in order to fulfill the thesis work. The plan will be delivered to a supervisory group for discussion and approval. During the second semester the student will pursue the thesis work. The thesis may be methodological in nature and contribute to the development of methods and techniques in micro-data analysis; or be practical in nature aimed at strengthening a part of an organizations’ business intelligence chain.
All courses are at advanced level belong to the main field, micro data analysis.
Term 1
Period 1
Artificial Intelligence, 7.5 credits
Statistical computing with R, 7.5 credits
Period 2
Data Collection and Data Quality, 7.5 credits
Business Intelligence, 7.5 credits
Term 2
Period 3 and 4
Data Mining, 7,5 hp
Spatial Data and Geographic Information Systems, 7.5 credits
Thesis work in Microdata Analysis, 15 credits
The Master Programme in Business Intelligence is given in English.
The programme name can, on request, reports in the diploma if students have successfully completed 75% of the programme’s courses and thesis work.
