Business Intelligence

Code

IT-BUI1

Version

3.0

Offered by

ICT Engineering

ECTS

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 based on the course assignment, which must be handed in before deadline.
Approximately 20 minutes incl. discussion of examinee's performance, without preparation.
Internal assessment.

Tools allowed:
N/A

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 12:00:00 AM

Course type

6. semester
7. semester
Compulsory for the specialization Data Engineering
Electives
Web 6 og 7