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2019/2020  BA-BDMAO1023U  Business Data Analytics, Quantitative Methods and Visualization

English Title
Business Data Analytics, Quantitative Methods and Visualization

Course information

Language English
Course ECTS 7.5 ECTS
Type Mandatory
Level Bachelor
Duration One Semester
Start time of the course Spring
Timetable Course schedule will be posted at calendar.cbs.dk
Study board
BSc in Digital Management
Course coordinator
  • Daniel Hardt - Department of Management, Society and Communication (MSC)
Main academic disciplines
  • Information technology
  • Statistics and quantitative methods
Teaching methods
  • Blended learning
Last updated on 11-12-2019

Relevant links

Learning objectives
  • Understand and deploy techniques for exploring and analyzing structured data
  • Understand and deploy basic machine learning techniques for classification and regression
  • Understand and deploy techniques for visualizing and presenting results of data analytics
  • Demonstrate an analytical understanding of business, societal, and ethical issues in the application of data analysis techniques
Business Data Analytics, Quantitative Methods and Visualization:
Exam ECTS 7,5
Examination form Oral exam based on written product

In order to participate in the oral exam, the written product must be handed in before the oral exam; by the set deadline. The grade is based on an overall assessment of the written product and the individual oral performance.
Individual or group exam Oral group exam based on written group product
Number of people in the group 2-4
Size of written product Max. 15 pages
Assignment type Written assignment
Written product to be submitted on specified date and time.
15 min. per student, including examiners' discussion of grade, and informing plus explaining the grade
Grading scale 7-point grading scale
Examiner(s) Internal examiner and second internal examiner
Exam period Summer
Make-up exam/re-exam
Same examination form as the ordinary exam
Course content, structure and pedagogical approach

This course is designed to equip students with practical knowledge of tools and techniques for the exploration, analysis and visualization of data in business. It also deals with conceptual, societal and ethical issues associated with these techniques. 


The course has a blended format, with some lectures presented online, together with associated online activities. In addition, there will be regular hands-on lab sessions. The course includes an independently chosen project, which will  take the form of a business case analysis. Students will select a dataset, to which they apply data science techniques, building relevant models and assessing them from a business and data science perspective.


The course will cover the following main topic areas:

  • Basic techniques for analysis of structured data, including use of query languages
  • Basic machine learning tools and techniques, including classification and regression, as well as unsupervised methods such as clustering
  • Techniques for visualization and presentation of the results of data analysis
  • Conceptual, societal and ethical issues with business data analytics
Description of the teaching methods
A mixture of face to face and online lectures, other online activities such as quizzes, group work, and practical exercises in hands-on sessions
Feedback during the teaching period
Regular feedback on hands-on exercises, automatic feedback on quizzes, in-class feedback on group work
Student workload
Lectures 30 hours
Readings and class preparation 116 hours
Exam Project and Preparation for Exam 60 hours
Last updated on 11-12-2019