Print
Code
IT-BUI1
Version
3.0
Offered by
ICT Engineering
ECTS
5
Prerequisites
DBS1 or a similar course (fundamentals of database systems)
Main purpose
Business intelligence is the delivery of accurate, useful information to the appropriate decision makers within the necessary time frame to support effective decision making.
The main purpose of the course is to equip the student to work with realistic business data using professional business intelligence tools in order to develop analytical solutions for businesses.
Knowledge
Students will obtain knowledge about understanding, reading, and presenting data from a dimensional model (such as a star schema or data cube) and other data models.
- Knowledge about building data products for operational vs real-time systems
Skills
- Data migration using data integration tools
- Create Data pipelines to cleanse data and move it into a data warehouse
- Create KPIs and measures
- Create data analyses, presentations and dashboards with Business Intellligence tools
- Create data structures for analysis purposes with selected tools
- Create, deploy and manage reports
Competences
- Evaluate pros/cons of different BI products, architectures and approaches
Topics
Teaching methods and study activities
Lessons alternate between theory and practical exercises. The course contains one compulsory assignment.
Expected workload for students is estimated to 135 hours.
Resources
Online resources and books (to be announced)
Evaluation
Examination
Exam prerequisites:
None
Type of exam:
Oral exam, 20 minutes, grading included.
Exam is without preparation.
During the semester, the student must prepare a course assignment within the curriculum, which must be submitted on WISEflow prior to the exam.
For the oral exam the discussion will be based on the course assignment.
The final grade will be based on an overall assessment of the assignment and the oral examination.
Internal assessment.
Tools allowed:
All
Re-exam:
Same as the ordinary exam
Grading criteria
Grading based on the Danish 7-point scale.
Additional information
Responsible
Knud Erik Rasmussen (kera)
Valid from
2/1/2024 12:00 AM
Course type
6. semester<br/>7. semester<br/>Elective for the specialization Data Engineering<br/>Electives<br/>Web 6 og 7<br/>
Keywords