Business Intelligence

Programme Structure

1. semester

• Business Intelligence and Data Management (10 ECTS)
• IS Development and Implementation in a Business Context (5 ECTS)
• Business Forecasting (10 ECTS)
• R for Business Analytics (5 ECTS)

2. semester

• Data Mining for Business Decisions (10 ECTS)
• Advanced Market Research (5 ECTS)
• Bayesian Networks (5 ECTS)
• Applied Data Science (10 ECTS)

3. semester

• Elective Courses (30 ECTS)

4. semester

• Master's Thesis (30 ECTS)

PREREQUISITE COURSES

In the first semester you follow the prerequisite courses that form the methodological and academic basis for the further study programme.
Business Forecasting is designed to give a solid theoretical and applied background to graduate students in forecasting. The course will not only be a methodology course but equally an applied course in which students will develop skills to approach business life situations critically, evaluate and communicate their findings with ease.
IS Development & Implementation in a Business Context introduces a range of methods and techniques that can be used to understand, plan and execute the processes in which information systems are developed, implemented, evaluated and modified, to enable the student to participate in the development, acquisition and implementation of information systems.
Data Warehousing provides the student with knowledge about the wide variety of database management systems available for a data warehouse solution and how to choose a solution that is relevant for the business intelligence project in question.
R and SQL for Business Analytics provides the student with skills to conduct proper data analysis using some of the most flexible environments available. Focus will be on data management and data manipulation with the purpose of preparing for a statistical analysis.

SPECIALISATION COURSES

In the second semester, you follow the specialisation courses of the programme.

Data Mining for Business Decisions teaches students how to work with large datasets and how relationships in such data can be detected with the purpose of transforming data into knowledge. Business applications cover a broad variety ranging from marketing to accounting, logistics and supply chain management.
In Advanced Market Research, the focus is on analytical customer relationship management. The course is devoted to customer-based analysis and predictive modelling with a primary focus on customer lifetime value and customer retention.
Bayesian Networks aim to awake the student's interest of the BN topic, by starting from their level of understanding and putting the subject into perspective by creating instances of its practical value.
Social Network Analytics and Text Mining covers processing and analysis of two types of data, which are increasingly available today; text data (written natural language) and data from social networks. Both types of data require techniques beyond “normal” quantitative methods.
In the third semester, you can choose elective courses within your areas of interest. The courses can be taken either at Aarhus BSS during the semester, at the AU Summer University or at one of our more than 200 partner universities abroad. You can also participate in internship programmes either in Denmark or abroad.
The fourth semester is devoted to the Master's thesis. You may freely choose the topic of the thesis and thereby get a chance to concentrate on and specialise in a specific field of interest. The thesis may be written in collaboration with another student or it may be the result of your individual effort. When the thesis has been submitted, it is defended before the academic advisor as well as an external examiner.