Data Warehousing





Offered by

ICT Engineering




Main purpose

The course will give the student a general familiarity with the processes, concepts and uses of data warehousing in both business and technical applications. The main focus of the course is practical techniques and methods for designing and implementing coherent data warehouse structures and data flows.




  • Demonstrate an understanding of the business motivations for data warehousing and be able to identify examples of the business value of information hidden in the data of operational systems
  • Understand the difference in design principles for operational (transaction processing) systems and systems for supporting ad-hoc querying
  • Understand the relationship and difference between dimensional database modelling and traditional entity-relational modelling
  • Apply knowledge of dimensional database modeling to design databases optimized for querying
  • Perform overall architectural design of a data warehouse, based on an understanding of the architectural components such as back room, front room, operational data stores, data marts, data staging areas, metadata etc.
  • Demonstrate knowledge of different tools and techniques available to implement data flows in a data warehouse, including a working knowledge of at least one major ELT tool.
  • Plan, design and implement Extract, Clean-up, Transform and Load data flows from multiple sources into a data warehouse.
  • Understand and apply knowledge of performance optimization and security in a data warehouse.
  • Be aware of the general business, ethical and social aspects of the use of Data Warehousing with respect to topics such as data credibility, electronic privacy etc.


  • Business motivations for data warehousing
  • Design principles for operational (transaction processing)
  • Dimensional database modelling and traditional entity- relational modelling
  • Architectural design of a data warehouse
  • Tools and techniques available to implement data flows in a data warehouse
  • Plan, design and implement Extract, Clean up, Transform and Load data flows
  • Performance optimization and security in a data warehouse
  • General business, ethical and social aspects of the use of Data Warehousing.

Teaching methods and study activities

  • Activities in the course will consist of 50 % classroom activities and 50 % individual/group work on a set case.

  • Required workload for students is estimated to 135 hours.


  1. [DWLT]: Kimball, Ralph The Data Warehouse Lifecycle Toolkit . 2nd edition.

  2. Supplementary notes.


External examination.
Evaluation will include presentation and discussion of course work at the oral exam.


‚ÄčThe exam is oral and it takes 20 minutes per student.

The examination is based on a drawn question from the theory of the course, and a discussion of how the theory was applied in course work. A single grade is given, comprising evaluation of both theory discussion and presented course work.

Grading criteria

According to the 7-point grading scale.

Mark 12:
Awarded to students who have shown excellent comprehension of the above-mentioned competences. A few minor errors and shortfalls are acceptable.

Mark 02
Awarded to students for the just acceptable level of comprehension of the required competences.

Additional information



Bo Brunsgaard

Valid from

2/1/2020 12:00:00 AM

Course type

6. semester
7. semester
Elective for the specialization Data Engineering


Big Data, Data Analysis, Decision Support, Systems Architecture, Dimensional Data Modelling, ETL Design