GRA 4147 Internship for Business Analytics
GRA 4147 Internship for Business Analytics
THIS COURSE WILL BE OFFERED AS A RE-SIT EXAMINATION ONLY IN SPRING 2025.
The internship is an opportunity to work full-time at a company during your studies and gain professional experience. This is particularly important for a programme like Business Analytics, an area in which companies have developed state-of-the-art technology and analytical tools for many relevant business problems. The internship will give you valuable insights in real-world challenges, and should help you in applying your academic background toward increasing organizational effectiveness and growth.
Note that in order to get a BI Internship approved as part of the degree, the student needs to apply according to BI’s procedures and submit a valid Learning Contract prior to starting his/her internship and in due time before the deadline.
At the end of the internship, the student should know the specific challenges faced by companies in using analytics to create value, both for the company and for its relevant stakeholders.
The overall goal of the internship is to increase the employability of the students. More specifically, at the end of the internship, the student should have acquired an understanding of:
- the practical issues and dilemmas faced by data-driven companies
- the data value chain and how it can be used to develop a competitive advantage
- the implications of using data in decision-making for the company’s data infrastructure and organizational culture and structure, and
- the time and efficiency constraints imposed by competition
The student at the end of the internship is expected to acquire skills in relation to:
- career management and job seeking
- defining and executing tasks under conditions of uncertainty, change and time pressure
- supporting suggestions for practical solutions with sound argumentation and grounded in analytics
- applying theoretical and technical knowledge to specific tasks and problems
The student should reflect on the complexity of the work environment, the market forces that drive businesses and how companies create value based on analytics in view of new opportunities, innovation and growth.
See teaching and learning activities.
Students will work full time for a minimum of 10 weeks (400 hours) in a company or organization. The internship may be paid or unpaid. Tasks are assigned by the company/organization and students must attend work as agreed upon. The internship will have to be completed by the end of week 43.
Students are also expected to participate in the following activities:
- Online employability course prior to the application process– compulsory
- Individual supervision – up to three hours
- Internship kick-off session – up to 1 hour
- Term paper guidance session – up to 1 hour
- Reflection seminar – up to 4 hours
- For further information about the application process, links to the Learning Contract and the Career Portal where BI Internship positions are posted, and relevant dates/resources regarding the BI Internship course, please visit the Student Portal.
- The internship is for a minimum of 10 weeks, full time. A completed, approved internship will give 18 ECTS credits only when the student has passed the reflection note and presentation.
- Each student must write a reflection note and hold a presentation individually.
Software tools: The required computer-based tools depend on the type of position the student will be working in. These requirements will be communicated by the employer in the position announcements.
All parts of the assessment must be passed in order to get a grade in the course.
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.
Disclaimer
Deviations in teaching and exams may occur if external conditions or unforeseen events call for this.
Participation requires that you have no pending courses and that you secure your own internship. See the student portal for detailed practical information.
| Assessments |
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Exam category: Submission Form of assessment: Submission PDF Exam/hand-in semester: First Semester Weight: 50 Grouping: Individual Duration: 1 Semester(s) Exam code: GRA 41471 Grading scale: Pass/fail Resit: Examination next semester, thereafter when next scheduled course |
Exam category: Activity, Oral Form of assessment: Presentation Exam/hand-in semester: First Semester Weight: 50 Grouping: Individual Comment: In the oral presentation, the student is expected to: 1) present general information about the company and the department that (s)he was assigned to, as well as the overall professional experience gained, 2) present specific outcomes related to the data-related internship project, and answer questions that demonstrate the ability to relate the internship experience with the academic knowledge acquired during the programme. Exam code: GRA 41472 Grading scale: Pass/fail Resit: Examination next semester, thereafter when next scheduled course |
All exams must be passed to get a grade in this course.
A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore acourse of 18 ECTS credit corresponds to a workload of at least 480 hours.
The reflection note (max 10 pages) should cover the following:
1) A description of what you did during the internship.
2) A reflection on your experiences.
The latter includes answers to questions like how did the internship affect your personal growth, what was useful (and what was not), how did the internship connect to your studies, and how did you grow professionally?
A mandatory part of your report is to conduct a mapping of the analytics maturity of the organization. This involves using the Delta Plus Model, developed by IIA (International Institute of Analytics) to conduct the mapping. You will be provided with relevant material for the mapping exercise by August.
Students submit the analytics maturity assessment and a company evaluation together with their paper.