Description
Data Modeling Solutions for Data Warehousing and Business Intelligence
Data Warehousing and Business Intelligence
Kennnummer Workload
180 Std.
Credits/LP
6
Studiensemester
2
Häufigkeit
des Angebots
Nur Wintersemester
Dauer
1 Semester
1 Lehrveranstaltungen
a) Data Warehousing and Business
Intelligence
Sprache
a) Englisch
Kontaktzeit
a) 45 Std.
Selbststudium
a) 135 Std.
geplante Gruppengröße
a) 15
2 Lernergebnisse/Kompetenzen
Nachdem das Modul erfolgreich absolviert wurde können die Studierenden …
Wissen (1)
... Demonstrate a broad and integrated knowledge and understanding of the concepts, technologies, and issues associated
with data warehousing environment and business intelligence.
Verständnis (2)
... Understand process characteristics of data warehouse environment and business intelligence applications.
... Classify the relevant types of technological and business aspects and drivers.
Anwendung (3)
... Use a range of routine and specialist skills and techniques to design and implement an application capable of providing
business intelligence.
... Select and apply appropriate methodological and architectural needs to define business case and business intelligence
prototype.
Analyse (4)
... Analyse selected data warehouse environment and business intelligence needs, described in a case studies (As-is and to-
be concept, excel prototype) .
Synthese (5)
... Implementing business case concept by using business intelligence software.
Evaluation / Bewertung (6)
... Evaluate opportunities and threads of BI usage and implementation.
... Offer professional level insights, interpretations and solutions to problems and issues associated with the development of a
data warehousing environment and business intelligence applications for a given case by using software well known in todays
business environment.
3 Inhalte
a) - Data Warehousing Perspectives
- Business Case and BI Project Management
- Data Warehouse Technical Architecture
- Data Attributes and Dimensional Data Modelling
- Data Governance and Metadata Management
- Data Sources and Data Quality Management
- Data Integration
- Business Intelligence Operations and Tools
- Presenting Data: Scorecards and Dashboards
- Testing, Rolling Out, and Sustaining the Data Warehouse
4 Lehrformen
a) Seminar
5 Teilnahmevoraussetzungen
- Basic principles in business administration and business information systems.
- Basic principles in database systems.
6 Prüfungsformen
a) Prüfungsleistung 1K (50 %)
a) Prüfungsleistung 1sbA (50 %)
7 Verwendung des Moduls
Business Consulting M.Sc. (BCM)
8 Modulbeauftragte/r und hauptamtlich Lehrende
Prof. Dr. Monika Frey-Luxemburger (Modulverantwortliche/r)
9 Literatur
a) Imhoff, Claudia; Galemmo, Nicholas; Geiger, Jonathan G.: Mastering data warehouse design : relational and
dimensional techniques, Wiley 2003
Inmon, William H.: Building the data warehouse, 4. ed., Wiley 2005
Kimball, Ralph; Caserta, Joe: The data warehouse ETL toolkit : practical techniques for extracting, cleaning,
conforming, and delivering data, Wiley 2004
Kimball, Ralph; Ross, Margy: The data warehouse toolkit : the complete guide to dimensional modeling, 2. ed., Wiley
2002
Moss, Larissa Terpeluk; Atre, Shaku: Business intelligence roadmap : the complete project lifecycle for decision-
support applications, Addison-Wesley 2003
doc_793116553.pdf
Data Modeling Solutions for Data Warehousing and Business Intelligence
Data Warehousing and Business Intelligence
Kennnummer Workload
180 Std.
Credits/LP
6
Studiensemester
2
Häufigkeit
des Angebots
Nur Wintersemester
Dauer
1 Semester
1 Lehrveranstaltungen
a) Data Warehousing and Business
Intelligence
Sprache
a) Englisch
Kontaktzeit
a) 45 Std.
Selbststudium
a) 135 Std.
geplante Gruppengröße
a) 15
2 Lernergebnisse/Kompetenzen
Nachdem das Modul erfolgreich absolviert wurde können die Studierenden …
Wissen (1)
... Demonstrate a broad and integrated knowledge and understanding of the concepts, technologies, and issues associated
with data warehousing environment and business intelligence.
Verständnis (2)
... Understand process characteristics of data warehouse environment and business intelligence applications.
... Classify the relevant types of technological and business aspects and drivers.
Anwendung (3)
... Use a range of routine and specialist skills and techniques to design and implement an application capable of providing
business intelligence.
... Select and apply appropriate methodological and architectural needs to define business case and business intelligence
prototype.
Analyse (4)
... Analyse selected data warehouse environment and business intelligence needs, described in a case studies (As-is and to-
be concept, excel prototype) .
Synthese (5)
... Implementing business case concept by using business intelligence software.
Evaluation / Bewertung (6)
... Evaluate opportunities and threads of BI usage and implementation.
... Offer professional level insights, interpretations and solutions to problems and issues associated with the development of a
data warehousing environment and business intelligence applications for a given case by using software well known in todays
business environment.
3 Inhalte
a) - Data Warehousing Perspectives
- Business Case and BI Project Management
- Data Warehouse Technical Architecture
- Data Attributes and Dimensional Data Modelling
- Data Governance and Metadata Management
- Data Sources and Data Quality Management
- Data Integration
- Business Intelligence Operations and Tools
- Presenting Data: Scorecards and Dashboards
- Testing, Rolling Out, and Sustaining the Data Warehouse
4 Lehrformen
a) Seminar
5 Teilnahmevoraussetzungen
- Basic principles in business administration and business information systems.
- Basic principles in database systems.
6 Prüfungsformen
a) Prüfungsleistung 1K (50 %)
a) Prüfungsleistung 1sbA (50 %)
7 Verwendung des Moduls
Business Consulting M.Sc. (BCM)
8 Modulbeauftragte/r und hauptamtlich Lehrende
Prof. Dr. Monika Frey-Luxemburger (Modulverantwortliche/r)
9 Literatur
a) Imhoff, Claudia; Galemmo, Nicholas; Geiger, Jonathan G.: Mastering data warehouse design : relational and
dimensional techniques, Wiley 2003
Inmon, William H.: Building the data warehouse, 4. ed., Wiley 2005
Kimball, Ralph; Caserta, Joe: The data warehouse ETL toolkit : practical techniques for extracting, cleaning,
conforming, and delivering data, Wiley 2004
Kimball, Ralph; Ross, Margy: The data warehouse toolkit : the complete guide to dimensional modeling, 2. ed., Wiley
2002
Moss, Larissa Terpeluk; Atre, Shaku: Business intelligence roadmap : the complete project lifecycle for decision-
support applications, Addison-Wesley 2003
doc_793116553.pdf