Data Mining for Business Intelligence
- Typ: Seminar (S)
- Semester: WS 13/14
- Dozent: Bagher Mirashrafi
- SWS: 2
- LVNr.: 2521030
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Hinweis:
Topics of this seminar are:
1-Data mining for business applications
2-Decision support systems and business intelligence
3-Multiple criteria decision making in data mining
4-Dynamic data mining and business applications
5-Customer relationship management decisions by data mining
In this seminar have been found: Accessible through the careful definition and introduction of each concept, followed by the extensive use of examples and numerous real-life case studies. To utilize mathematical models and analysis models to make effective and good quality business decisions. A practical guide to the mathematical models and analysis methodologies of business intelligence.
Bemerkungen:
Anmeldung :To register for this seminar by e-mail is required. Interested persons please contact the seminar leader ( mirashrafi@statistik.uni-karlsruhe.de ).
Anmeldung: 1.10.2013
Anmeldungsschluss: 01.11.2013
Für weitere Informationen : http://statistik.econ.kit.edu/
Beschreibung:
Business intelligence is a broad category of applications and technologies for gathering, providing access to, and analyzing data for the purpose of helping enterprise users make better business decisions. The term implies having a comprehensive knowledge of all factors that affect a business, such as customers, competitors, business partners, economic environment, and internal operations, therefore enabling optimal decisions to be made.
Literaturhinweise (en):
1. Han, J., Kamber, M., & Pei, J. (2011). Data mining: concepts and techniques, 3rd ed . Morgan Kaufmann.
2. Shmueli, G., Patel, N. R., & Bruce, P. C. (2008). Data mining for business intelligence: Concepts, techniques, and applications in Microsoft Office Excel with XLMiner. Wiley. com.
3. Turban, E., Aronson, J., & Liang, T. P. (2005). Decision Support Systems and Intelligent Systems 7”‘Edition. Pearson Prentice Hall.
4. Vercellis C. (2009). Business Intelligence: Data Mining and Optimization for Decision Making. John Wiley & Sons Ltd.
5. Berry, M. J., & Linoff, G. S. (2004). Data mining techniques: for marketing, sales, and customer relationship management. Wiley. com.
Kommentar:
Topics of this seminar are:
1- Data mining for business applications
2- Decision support systems and business intelligence
3- Multiple criteria decision making in data mining
4- Dynamic data mining and business applications
5- Customer relationship management decisions by data mining
In this seminar have been found: Accessible through the careful definition and introduction of each concept, followed by the extensive use of examples and numerous real-life case studies. To utilize mathematical models and analysis models to make effective and good quality business decisions. A practical guide to the mathematical models and analysis methodologies of business intelligence.