13840 - Data Warehouses Modulübersicht

Module Number: 13840
Module Title:Data Warehouses
  Data-Warehouse-Technologien
Department: Faculty 1 - Mathematics, Computer Science, Physics, Electrical Engineering and Information Technology
Responsible Staff Member:
  • Prof. Dr.-Ing. habil. Schmitt, Ingo
Language of Teaching / Examination:English
Duration:1 semester
Frequency of Offer: Every summer semester
Credits: 6
Learning Outcome:After successfully completing the module, students will have acquired knowledge and capability to design, model, and to optimize a data warehouse.
Contents:Data is frequently stored redundantly and is distributed over several data sources in an enterprise. Data quality is usually low. Analyzing data should be made possible.
The course gives an introduction into the architecture and processes of data warehouse systems. Focus is on database aspects including design, modelling, ETL-processes, querying and optimization.

Acquired knowledge will be applied within a project.

This module builds on existing database knowledge. In particular, expertise in SQL, normalization theory and  database design is needed.
Recommended Prerequisites:The module cannot be successfully completed without knowledge of the content of
  • 12330 Datenbanken
Mandatory Prerequisites:No successful participation in module 14459 Data-Warehouse-Technologien.
Forms of Teaching and Proportion:
  • Lecture / 2 Hours per Week per Semester
  • Exercise / 1 Hours per Week per Semester
  • Laboratory training / 1 Hours per Week per Semester
  • Self organised studies / 120 Hours
Teaching Materials and Literature:
  • A. Bauer, H. Günzel: "Data Warehouse Systeme -- Architektur, Entwicklung, Anwendung": 3. Auflage, dpunkt.verlag, Heidelberg, 2009
  • W. Lehner: "Datenbanktechnologie für Data-Warehouse-Systeme": dpunkt.verlag, Heidelberg, 2003
  • W.H. Inmon: "Building the Data Warehouse": Wiley & Sons, New York, 1996
  • G. Saake, A. Heuer, K. Sattler: "Datenbanken: Implementierungstechniken": 2. Auflage, mitp-Verlag, Bonn, 2005
  • R. Kimball, L. Reeves, M. Ross, W. Thornthwaite: The Data Warehouse Lifecycle Toolkit": Wiley & Sons, New York, 1998
Module Examination:Prerequisite + Final Module Examination (MAP)
Assessment Mode for Module Examination:Prerequisite:
  • successful completion in practical training tasks and in exercises tasks
Final module examination:
  • Written examination, 120 min. OR
  • Oral examination, 30-45 min. (with small number of participants)
In the first lecture it will introduced, if the examination will organized in written or oral form.
Evaluation of Module Examination:Performance Verification – graded
Limited Number of Participants:80
Part of the Study Programme:
  • Master (research-oriented) / Artificial Intelligence / PO 2022
  • Abschluss im Ausland / Betriebswirtschaftslehre / keine PO
  • Abschluss im Ausland / Elektrotechnik / keine PO
  • Abschluss im Ausland / Maschinenbau / keine PO
  • Master (research-oriented) / Mathematical Data Science / PO 2025
  • Bachelor (research-oriented) / Wirtschaftsinformatik / PO 2024
Remarks:
  • Study programme Artificial Intelligence M.Sc.: Compulsory elective module in complex  „Knowledge Acquisition, Representation, and Processing“
Module Components:
  • Lecture: Data Warehouses
  • Accompanying exercises (with integrated laboratory)
  • Related examination
Components to be offered in the Current Semester: