course-details-portlet

AE302319 - Business analytics

About

Examination arrangement

Examination arrangement: Aggregate score
Grade: Letter grades

Evaluation Weighting Duration Grade deviation Examination aids
Individual project assignment 60/100
Portfolio in groups 40/100

Course content

Technological advancement provide increasingly better access to detailed and complex data sources and new opportunities for gathering and using data sources in integrated decision support systems. Big data, business intelligence and business analytics are buzzwords that represent different aspects of this development. This advancement in technology also goes towards intuitive user interfaces that are increasingly making tools available for advanced use for people without detailed knowledge of the technology itself, but who understand the technology at an overall conceptual level. This provides new opportunities for specialists to use technology to tailor decision support for financial and strategic purposes. The purpose of this course is to provide students with good insight into the possibilities for decision support using newer technologies with updated examples from business.

Learning outcome

Knowledge:

  • Provide basic knowledge about central concepts within business analytics.
  • Able to explain the reason for and importance of business analytics.
  • Describe central concepts within the field.
  • Familiarity with business analytics tools

Skills:

  • Use business analytics to support financial and business decisions.
  • Describe problem areas related to business analytics.
  • Actively participate in discussions and decisions concerning business analytics in a given organization.

General competence:

  • Relate business analytics to other fields covered within the bachelor study program
  • Relate business analytics to central business functions.
  • Use insight from the course to use business analytics.

Learning methods and activities

Lectures, videos, analytic tools, cases and programming exercises.

Further on evaluation

Exam:

- Portfolio in groups that counts 40% of final grade.

- Individual project assignment that counts 60% of final grade.

There will be no resit exam.

If a student passes the portfolio exam but fails on the individual project assignment, he/ she can retake only the individual project assignment on the next ordinary exam to get a final grade.

If a student passes the individual project assignment but fails the portfolio exam, he/ she must retake both examination parts on the next ordinary exam period.

Course materials

Selected cases and data sets.

Sharda, Delen, Turban: Business Intelligence, Analytics, and Data Science: A Managerial Perspective, 4th edition (Pearson)

More on the course

No

Facts

Version: 1
Credits:  7.5 SP
Study level: Third-year courses, level III

Coursework

Term no.: 1
Teaching semester:  SPRING 2024

Language of instruction: English

Location: Ålesund

Subject area(s)
  • Strategy and Management
  • Economics and Administration
  • Management Accounting and Control
Contact information
Course coordinator:

Department with academic responsibility
Department of International Business

Timetable

List view
Calendar view

Examination

Examination arrangement: Aggregate score

Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
Spring ORD Portfolio in groups 40/100 INSPERA
Room Building Number of candidates
Spring ORD Individual project assignment 60/100 INSPERA
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
Examination

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

More on examinations at NTNU