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Business Intelligence

Business Intelligence

Code: BIG4TF022
Extent: 5 credits (135 h)
Semester: 3
Language: English
Level: Profile studies
Type: Compulsory / Optional

Learning outcome
Upon successful completion of the course, the student

  1. understands the importance of Business Intelligence in
    today's competitive business environment
  2. is familiar with the basic concepts, ETL-process and technics used in the business environment
  3. has gained skills and competence in using market leading BI tools for creating solutions and
    analysing business information and data

Content
The main topics of this course are as follows:

  • main concepts and introduction to Business Intelligence
  • business value as a driver and BI maturity
  • the ETL process in practice
  • using of market leading tools to extract data and create data models
  • introduction to agile development in BI
     

Starting Level and linkage with other courses
No prerequisites.

Assessment
The evaluation scale for an accepted course contains grades 1 to 5.

Grade 1

The student:

  1. has a basic understanding of the importance of Business Intelligence
  2. is familiar with at least some of the basic concepts, architectures, methodologies,
    strategies, tools or technics in BI
  3. has basic skills in using market leading BI tools for analysing business information
    and data

Grade 3

      The student:

  1. has a good understanding of the importance of Business Intelligence
  1. is quite familiar with at least some of the basic concepts, architectures, methodologies,
    strategies, tools or technics in BI
  2. has some skills in using market leading BI tools for analysing business information
    and data

Grade 5

      The student:

  1. has a very good understanding of the importance of Business Intelligence
  1. is very familiar with at least some of the basic concepts, architectures, methodologies,
    strategies, tools or technics in BI
  2. has good skills in using market leading BI tools for analysing business information
    and data

Working life connections
Guest lecture
 

Internationality
The software tools and languages used on the course are international. The language of the course material is mainly in English. Students from many nationalities work together in the analysis project.

Learning methods
The learning methods of this course are as follows:

a. E-learning course with possibility to class sessions
b. Module based self-study - hands-on, videos etc and/or
c. Module based tasks where students demonstrate gained skills and competence and/or
d. Exam in Exam-system and/or
e. On-the-job learning and reporting and/or
f. A combination of a – e.

This course accepts enrolments after the normal enrolment period.
The course can be done by e-learning / distance study.
Every student creates and follows an individual study plan.
The course appreciates individual focus and approaches.

Responsible teacher
Ralf Rehn