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2013/2014  KAN-CMIT_VDAW  Data warehouses

English Title
Data warehouses

Course information
Language English
Exam ECTS 7.5 ECTS
Type Elective
Level Full Degree Master
Duration One Quarter
Course period First Quarter
Changes in course schedule may occur
Monday 09.50-12.35, week 36-43
Time Table Please see course schedule at e-Campus
Study board
Study Board for BSc/MSc in Business Administration and Information Systems, MSc
Course coordinator
  • Lars Frank - Department of IT Mangement (ITM)
Administrative contact person is Bodil Sponholtz, ITM (bsp.itm@cbs.dk)
Main academic disciplines
  • Information Systems
  • Management of Information and Knowledge Management
  • Supply Chain Management and Logistics
  • Financial and management accounting
Last updated on 14-11-2013
Learning objectives
The objective of the course is to qualify the students for occupation within designing and using Business Intelligence (BI)/decision support systems. That is:
  • For each node in the value chain of any type of organization, the student should be able to design, describe, and implement a data mart for decision making.
  • As a datawarehouse normally evolves over time, the student should also be able to demonstrate how “conforming” the data warehouse can protect the investment against new unforeseen demands to the data warehouse.
  • The studenst should be able to demonstrate how to make decision support systems for different types of decision problems.
Examination
Oral exam on the basis of a mini project (group):
Examination form Oral exam based on written product

In order to participate in the oral exam, the written product must be handed in before the oral exam; by the set deadline. The grade is based on an overall assessment of the written product and the individual oral performance.
Individual or group exam Individual
Size of written product Max. 15 pages
Assignment type Project
Duration
Written product to be submitted on specified date and time.
20 min. per student, including examiners' discussion of grade, and informing plus explaining the grade
Preparation time No preparation
Grading scale 7-step scale
Examiner(s) Internal examiner and second internal examiner
Exam period Autumn Term
Make-up exam/re-exam
Same examination form as the ordinary exam
Description of the exam procedure
Oral exam on the basis of a mini project (group). Max. 15 pages per 2-5 students. The mini project is written in parallel with the course. The student is not entitled to supervision. The date for handing in the project will be decided by the secretary.

20 minutes per student incl. performance discussion. No preparation for the oral exam. The teacher will act as examiner at the oral exam. 2nd examiner is internal (CBS).

Even if it is a group exam, each student must be assessed individually. The students do not need to give an account of which parts of the project they are responsible for. The mini project and the oral exam are both included in the overall assessment.

The title question(s) and content of the project must be prepared by the students within the framework of the syllabus, possibly together with the teacher. The oral examination will be based on a discussion and a perspective of the mini project. The examiner may ask questions that go beyond the project, but within the framework of the syllabus.

The re-exam takes place on the same conditions as the ordinary exam.
Course content and structure
As an introduction to the course the basic data models for both operative databases/On Line Transactional Processing (OLTP) and data varehuse/On Line Analytical Processing (OLAP) are described.The focus of the course is how to design, describe, implement, and evaluate data warehouses for different line of businesses/organisations. From a business point of view the main problem in data warehouse design is that most companies/organizations have lots of data, but these data are not structured in order to give information for decision support.
The course will also give an overview of the different types of data mining from a user point of view. Therefore, data mining algorithms will not bedescribed.
Teaching methods
The teaching is integrated with exercises and discussion of the solutions. The teaching also consists of supervising the project groups and discussion of the solutions followed by student presentation of their work with the mini project.
Expected literature
Kode Forfattere Titel Forlag Sider
LF0 L. Frank Slideshow in design of relational databases. The slideshow in design of relational databases will be uploaded in LEARN.   90 sider.
         
RK2 Ralph Kimball and Margy Ross The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling, 2nd Edition.
A digital copy is recommended.		 Wiley.
2002		 Første 370 sider.
LF1 L. Frank Databases and Applications with Relaxed ACID Properties.
Only chapters 8 and 10 are required readings and these chapters will be uploaded in LEARN.		 Copenhagen Business School.
2008. The book will be uploaded in LEARN.		 24
LF2 L. Frank Slideshow in data mining that will be uploaded in LEARN. Copenhagen Business School.
2012. The slideshow will be uploaded in LEARN.		 38
  Total:                522
Last updated on 14-11-2013