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Lecturer(s)
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Křupka Jiří, doc. Ing. PhD.
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Course content
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1. Principles and use of BI. 2. Data, information and knowledge. 3. System approach to decision making. 4. Advanced methods of multi-criteria decision making for certainty. 5. Decision-making methods with uncertainty. 6. Stages and tasks of CRISP-DM methodology. 7. Preparation of data for modelling. 8. Selected methods and basics of creating models. 9. Creation of selected models and their evaluation. 10. Database aspect in BI system design. 11. Technology, technical components and construction of the Decision Support System as a part of BI. 12. Modelling in BI. 13. New trends in BI and Competitive Intelligence.
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Work with text (with textbook, with book), Methods of individual activities
- Contact teaching
- 26 hours per semester
- Practical training
- 26 hours per semester
- Home preparation for classes
- 26 hours per semester
- Preparation for a credit (assessment)
- 26 hours per semester
- Preparation for an exam
- 32 hours per semester
- Preparation of a presentation (report)
- 14 hours per semester
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Learning outcomes
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The course aims are to introduce students with issues of Business Intelligence (BI). The course is focused on gaining knowledge, mastering procedures, mastering tools and developing skills in analysis, evaluation and reporting of data for the needs of effective work with company data, faster and more effective decision-making.
Students will be aware of the Business Intelligence issues, they will be able to explain the basis of methods and algorithms use in decision support system. They will be able to solve decision-making tasks using decision-making support tools. They will be familiar with the basic structure of these systems and the role of each component.
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Prerequisites
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unspecified
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Assessment methods and criteria
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Oral examination, Written examination, Work-related product analysis, Creative work analysis
Assignment is conditional to the following requirements: - minimum attendance at seminars in compliance with the relevant regulations - completion of continuous tasks at seminars - passing the final test at the final seminar The examination is written and oral that is in accordance with the Study and Examination Regulations at UPCE.
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Recommended literature
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Hand, David J. Intelligent data analysis : an introduction. Berlin: Springer, 2003. ISBN 3-540-43060-1.
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Harris, Carl M. Encyclopedia of operations research and management science. Boston: Kluwer Academic, 2001. ISBN 0-7923-7827-X.
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Ragsdale, Cliff T. Spreadsheet modeling & decision analysis : a practical introduction to management science. Mason: South-Western, 2004. ISBN 0-324-20305-5.
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Turban, Efraim. Decision support and business inteligence systems. Upper Saddle River: Pearson Prentice Hall, 2007. ISBN 0-13-198660-0.
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Turban, Efraim. Decision support systems and intelligent systems. New Jersey: Prentice Hall, 1998. ISBN 0-13-740937-0.
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