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Course content

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.




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Recipient: Dalarna University

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