GRA 4163 Consultancy Project for Data Science

GRA 4163 Consultancy Project for Data Science

Course code: 
GRA 4163
Accounting and Operations Management
Course coordinator: 
Pål Berthling-Hansen
Course name in Norwegian: 
Consultancy Project for Data Science
Product category: 
MSc in Data Science for Business
2023 Autumn
Active status: 
Level of study: 
Teaching language: 
Course type: 
One semester

This course will give students a sense of how to solve a problem for a concrete company or public entity. Students will experience first-hand how to solve a concrete business problem in groups acting as consultants. The assignments will depend on the problem at hand, but studnets can expect to use several of their skills from other courses, but with a strong focus on problem solving for a client.

Learning outcomes - Knowledge
  • After having completed this course, students should be familiar with tools and knowledge allowing them to solve a specific problem for a company/entity. The problems can be of national or international application.
  • Specifically students will obtain an understanding of how consultants work with analytical problems, and how such problems and solutions are presented to a client.
Learning outcomes - Skills
  • Students will identify a problem and analyse a dataset in order to apply specific statistical tools to solve the probllem.
  • Data management skills will also be required to turn data into information and further into insight. 
  • Through the application of previous learnt knowledge and skills, the students will experience writing a consultancy report and presenting the report to key decision makers.
  • Working in groups the students will experience and learn skills related to group related problem-solving.
  • Students will specifically learn how to scope a problem, how to analyse the problem at hand, and finally how to present the findings to a client.
General Competence
  • Students learn how to evaluate a business problem from several angles and will experience firsthand the importance of reflecting on how the suggested solution will add value to the organization and/or sustainability to the public sector through the suggested solutions.
  • The students have to be critical to any data provided and also need to critically evaluate their suggested solution.
Course content

The student groups are presented with data and a real problem from a concrete company or public entity. The data will be of a structured/semi structured format, and the inherent business problem will be roughly outlined. The students spend a total of 5 weeks applying various methods/tools to analyse the data in order to outline a suggested course of action for the business in question. The students provide a written report for evaluation.

During the course students will meet with individuals from consultancy companies sharing their insights into business analytic problem solving.

- Scoping a problem

- Analysing a business related problem using logic trees, decision trees, MECE, etc.

- Presenting the findings/solution/recommendation to a client

Teaching and learning activities

The learning process will be as follows (sequence changes may occur):

-          Handout of data/problem 1

-          Consultancy session 1 – How do consultants work?

-          Q/A session from the company/entity in question

-          Hand-in Solution 1

- All sessions will be held online as Webinars

Software tools
Software defined under the section "Teaching and learning activities".
Additional information

Please note that while attendance is not compulsory in all courses, it is the student’s own responsibility to obtain any information provided in class.

Students are expected to utilize software/digital tools previously learnt in the programme.


All courses in the Masters programme will assume that students have fulfilled the admission requirements for the programme. In addition, courses in second, third and/or fourth semester can have specific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.


Deviations in teaching and exams may occur if external conditions or unforeseen events call for this.

Exam categoryWeightInvigilationDurationGroupingComment exam
Exam category:
Form of assessment:
Written submission
Exam code:
GRA 41631
Grading scale:
Grading rules:
Internal examiner
Examination when next scheduled course
100No5 Week(s)Group/Individual (1 - 3)
Exam category:Submission
Form of assessment:Written submission
Grouping (size):Group/Individual (1-3)
Duration:5 Week(s)
Exam code:GRA 41631
Grading scale:ECTS
Resit:Examination when next scheduled course
Type of Assessment: 
Ordinary examination
Total weight: 
Student workload
24 Hour(s)
Group work / Assignments
100 Hour(s)
Prepare for teaching
24 Hour(s)
Student's own work with learning resources
12 Hour(s)
Sum workload: 

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 6 ECTS credits corresponds to a workload of at least 160 hours.