ITL31017 Business Intelligence (Spring 2019)
Facts about the course
- ECTS Credits:
- 10
- Responsible department:
- Faculty of Computer Science
- Course Leader:
- Cathrine Linnes
- Teaching language:
- English
- Duration:
- ½ year
The course is connected to the following study programs
Compulsory course in Bachelor in Information Systems.
Lecture Semester
4th semester (Spring).
The student's learning outcomes after completing the course
Knowledge
The student
- is able to describe and understands the need for Business Intelligence.
- has knowledge about and can use existing efficient visualization techniques and tools.
- knows the major frameworks of computerized decision support: analytics, decision support systems (DSS), and business intelligence (BI).
- knows the literature and can identify research areas in Business Intelligence and Analysis.
Skills
The student can
- use Business Intelligence to formulate and solve corporate problems and to support managerial decisions.
- use data analysis techniques to make better decisions.
- design and build new visualizations.
- work on BI development projects in a team environment.
General competence
The student understands
- different types of visualization techniques.
- the importance of data / information visualization.
- social networking and social analyses and their practical applications.
- the purpose and benefits of data mining.
Content
Organisations have an increasing availability of information, and Business Intelligence provides clever methods, technologies and strategies to manage the huge amount of data.
The course provides a broad introduction to the field Business Intelligence and Analysis. In this course, the students will gain a better understanding of both established and cutting-edge processes used to retrieve data and to turn this information to key resources for the organisation.
Forms of teaching and learning
Lectures, exercises and supervision.
Workload
Approx. 240 hours.
4 hours of lectures + practice per week
Coursework requirements - conditions for taking the exam
Up to 4 mandatory assignments submitted during the semester.
The coursework requirements must be approved before students may sit the exam.
Examination
Group project and individual written exam
A final grade is awarded on the basis of a two partial exams. Each partial exam must be passed in order to pass the whole course.
Partial exam 1 is a group project that counts 60%. Group grades are awarded for the project.
Partial exam 2 is an individual written exam based on the course curriculum that counts 40%. Duration 2 hours. No support materials permitted.
An overall individual final grade is awarded for the course using grading scale A to F.
Examiners
The exam is assessed by the course instructor and an internal or external examiner.
Conditions for resit/rescheduled exams
In the case of resit or rescheduled examinations, each part of the examination may be retaken. Partial exam 1 must be taken in connection with the next ordinary course examination.
In the case of resit and rescheduled examinations, the content of the group project must be agreed with the course instructor.
Course evaluation
This course is evaluated by a
- Mid-term evaluation (compulsory)
The responsible for the course compiles a report based on the feedback from the students and his/her own experience with the course. The report is discussed by the study quality committee of the faculty of Computer Sciences.
Literature
The reading list is last updated December 18, 2018.
Sharda, R., Delen, D., & Turban, E. (2018). Business Intelligence, Analytics, and Data Science: A Managerial Perspective (4th ed). Harlow, UK. Pearson. ISBN 978-1-292-22054-3