ITL31019 Business Intelligence (Spring 2020)

The course is connected to the following study programs

This course is compulsory in

• Bachelor in Information Systems (2018)

• Bachelor in Information Systems - Software Engineering and Business Intelligence

Elective course for others.

Recommended requirements

Knowledge equivalent to the course Database Systems/Databases.

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

• can articulate modern concepts, theories, and research in the field of Business Intelligence (BI)

• can discuss the social and ethical issues related to the use of Business Intelligence technologies in organizations

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

• work on BI development projects in a team environment

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. 250 hours.

4 hours of lectures + practice per week

Examination

Portfolio and individual written exam

A final individual 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: a portfolio comprising of up to 4 deliverables that counts 60 %. The deliverables (individual or in groups) must be delivered within given deadlines and according to specifications given by the course instructor. A grade will be awarded on the basis of an overall assessment. An individual grade is given using grading scale A to F.

Partial exam 2: individual written exam 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 portfolio 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 March 8th 2019.

Sharda, R., Delen, D., & Turban, E. (2018). Business Intelligence, Analytics, and Data Science (4th ed.). Pearson: Harlow, UK. ISBN: 978-1-292-22054-3