MSc in Business Administration and Data Science

This programme uniquely combines hard analytical skills with an understanding of the relevant business data context for application. Through this combination you will learn how to use theories, models and tools for data analytics to generate actionable insights and develop fact based platforms for decision making by conducting visual, text and predictive analysis.


Through a mix of theory and hands-on exercises you will learn to design, develop, implement, test and document technical business data analytics solutions to support organizational processes and/or satisfy business needs by using data analytics oriented programming languages (such as Python, R), Big data platforms (such as Hadoop, Spark) and open source technologies. You will work with visual, text and predictive analytic techniques including latest methodologies from data mining, machine learning and deep learning in order to transform Big data sets into business assets.

You will understand the role of data analytics in the digital economy, and how companies can deal with the challenges and opportunities provided by the increasing availability of data, which is changing the business landscape. This will allow you to understand both the strategic and operational impact digitalization has on business innovation and strategy. In combination with courses on visual analytics this will enable you to communicate across both the technical and the business side of business intelligence in both the development and presentation of solutions using business data analytics.

By working with the theoretical foundation as well as hands-on statistical analysis software packages (such as R. MATLAB, SAS) you will learn how to analyze and select the relevant method and model to perform predictive analysis and forecasting to produce fact based platforms for decision making.

Building on this foundation you will also learn about the international and national regulations and legislations for assessing and designing business data analytics solutions and products in accordance with the applicable legislation to ensure regulatory compliance and reflect on data ethics.

Programme Structure


Structure and Teaching

All courses will be designed in the blended learning format, and will use a mix of lectures and exercises with mandatory assignments throughout the courses.

Cand.Merc.Data Science’s core technical faculty will be drawn from the Centre for Business Data Analytics, and the Departments of Digitalization and Economics. Core Business faculty will be drawn from the Departments of Innovation, Strategic Management and Globalization, Management Politics and Philosophy and Law.

The new MSc programme will be supported by the purpose-built and student-dedicated CBS Business Data Analytics Cluster , which will feature a state-of-the-art hybrid architecture comprising an on-premises cluster of 40 compute nodes, large memory and very large storage paired with cloud servers to support dynamic scaling on demand for class exercises, exam projects and master theses. 

The below table lists the structure of the programme and the ECTS credits of the individual courses. 

1. semester 2. semester 3. semester 4. semester
Innovation and Strategy in the Digital Economy (7,5 ECTS) Data Economics (7,5 ECTS)

Electives / Internship / Exchange (30 ECTS)






Master's thesis (30 ECTS)







Datafication: Regulation, Governance, Security, Privacy and Ethics (7,5 ECTS) Natural Language Processing and Text Analytics (7,5 ECTS)
Foundations of Data Science: Programming and Linear Algebra (7,5 ECTS) Predictive Analytics (7,5 ECTS)
Visual Analytics (7,5 ECTS) Data Mining, Machine Learning and Deep Learning (7,5 ECTS)

You can find course descriptions in the programme study regulations.

Sidst opdateret: Web editor - Student Communications // 13/03/2023