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2019/2020  KAN-CCMVV4042U  Datafication – foundations, transformations and challenges

English Title
Datafication – foundations, transformations and challenges

Course information

Language English
Course ECTS 7.5 ECTS
Type Elective
Level Full Degree Master
Duration One Semester
Start time of the course Autumn
Timetable Course schedule will be posted at calendar.cbs.dk
Max. participants 170
Study board
Study Board for MSc in Economics and Business Administration
Course coordinator
  • Nanna Bonde Thylstrup - Department of Management, Society and Communication (MSC)
Main academic disciplines
  • Information technology
  • Communication
  • Organisation
Teaching methods
  • Blended learning
Last updated on 14-08-2019

Relevant links

Learning objectives
  • • Articulate central features of big data, including historical, regulatory, societal and technological developments
  • • Discuss and reflect on the potentials and challenges of relying on different types of data and algorithms in organizational settings
  • • Analyze the technical and conceptual issues associated with text and other forms of unstructured data
  • • Understand and contrast different theories and conceptualizations of big data and its ramifications in terms of ethics and governance
Course prerequisites
Datafication - Foundations, Transformations and Challenges:
Exam ECTS 7,5
Examination form Home assignment - written product
Individual or group exam Individual exam
Size of written product Max. 15 pages
Assignment type Written assignment
Duration Written product to be submitted on specified date and time.
Grading scale 7-point grading scale
Examiner(s) One internal examiner
Exam period Winter
Make-up exam/re-exam
Same examination form as the ordinary exam
* if the student fails the ordinary exam the course coordinator chooses whether the student will have to hand in a revised product for the re- take or a new project.
Course content, structure and pedagogical approach


This course offers students the advanced theoretical and analytical skills needed to articulate, develop and reflect critically on data-driven strategies in organizations. The course discusses the digital transformations that have led to the growing availability of and reliance on digital data and advanced algorithms, and includes a focus on societal, economic, regulatory and political dimensions, institutional developments and technological innovations. On this backdrop, the course looks at a variety of platforms and contexts where big data can be put to use in organization and strategy. This more practice- and strategy-oriented part focuses on various types of digital data, analytical methods and technologies, and reflects on the practical, strategic and theoretical opportunities and challenges they create. Finally, the course reflects on more overarching questions about knowledge, ethics, power and governance raised by big data.




Description of the teaching methods
The course combines lectures, guest lectures by big data professionals and practitioners, discussions, student presentations, and case studies in an engaging and participatory learning environment.
Feedback during the teaching period
Feedback takes a number of shapes in the course. We will discuss ideas for term papers throughout the course, students will be given tutorials and pre-tests, and there will be opportunities for students to engage in peer feedback.
Student workload
Lectures 33 hours
Exercises 20 hours
Preparations, readings and cases 90 hours
Exam assignment preparations 60 hours
Further Information

This course is a part of a minor in Data in Business

Expected literature



Last updated on 14-08-2019