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2020/2021  MA-MMFUV1004U  Big Data and Analytics

English Title
Big Data and Analytics

Course information

Language English
Course ECTS 6 ECTS
Type Elective
Level Part Time Master
Duration One Semester
Start time of the course Autumn
Timetable Course schedule will be posted at calendar.cbs.dk
Min. participants 10
Max. participants 30
Study board
Study Board for Master i forretningsudvikling
Course coordinator
  • Dana Minbaeva - Department of Strategy and Innovation (SI)
Main academic disciplines
  • Information technology
  • Organisation
  • Statistics and quantitative methods
Teaching methods
  • Blended learning
Last updated on 24-08-2020

Relevant links

Learning objectives
  • Knowledge about differences between big data vs. business data, big data analytics vs. business data analytics, and framework for business value generation from new technologies to your own company.
  • Skills in methods and tools for business data analytics in terms of visual, text and predictive analytics.
  • Competences to generate meaningful facts, actionable insights, valuable outcomes and sustainable impacts from business data sets.
Course prerequisites
Students should have basic knowledge of management and experience with Excel.
The course target managers and specialists working with, or interested in working with, external and internal data for different business functions such as Customer Segmentation, Human Capital Analytics, Predictive Maintenance etc. The course is also open for professionals who would like to understand the power of analytics and get knowledge about how to use data for evidence-based management decisions.
Big Data and Analytics:
Exam ECTS 6
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 Individual exam
Size of written product Max. 20 pages
Assignment type Synopsis
Written product to be submitted on specified date and time.
30 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 Winter and Summer
Make-up exam/re-exam Home assignment - written product
Size of written product: Max. 10 pages
Assignment type: Essay
Duration: Written product to be submitted on specified date and time.
Description of the exam procedure

Individual presentation based on a project report in the form of a PowerPoint.



Course content, structure and pedagogical approach

Most companies have accumulated a surfeit of business data: customer data, performance-related data, current and historic operational data, data from employees’ engagement surveys, etc. Yet, only few can make extensive use of data to drive evidence-based management decisions, support business development and transformation. Why so?


In addition to the need of owning data of a reasonable quality, developing a solid ground for evidence-based decisions requires having the right people, with the advanced analytical skills and scientific rigor in modeling and interpretation of the results.


The course provides participants with a deep understanding of the nature of big data and business analytics, and a practical toolkit on how to perform big data analysis. Our focus is on discovering different ways to generate business value from in-house and open big data sets for the purpose of increasing competitiveness in the global marketplace.


After having attended this course, you will gain knowledge about paradigms for generating competitive advantages and business value from new technologies. Furthermore, you will understand the logic behind business and big data analytics. The course also focuses on the importance of providing evidence to sustain managerial claims, applying an analytical process that covers all activities from problem formulation to result communication, and reflecting on and managing potential pitfalls.


You will be introduced to the Centre for Business Data Analytics framework for transforming big data sets into business assets by creating meaningful facts, actionable insights, valuable outcomes, and sustainable impacts. Building on the experience of Human Capital Analytics Group at CBS, you will learn about the different kinds of human capital analytics projects that can be carried out on corporate data. Projects that supports corporate transformation and business development by linking people and performance.

Description of the teaching methods
Blended Learning, Interactive lectures, Hands-on exercises, “Show-and-Tell” Demos, and In-Class Project Work.
Feedback during the teaching period
Feedback during class is possible.
Student workload
Preparation 132,5 hours
Teaching hours 32 hours
Exam 0,5 hours
Last updated on 24-08-2020