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Lecturer(s)
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Juříková Martina, Ing. Ph.D.
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Course content
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- Data mining, Big data, the meaning of "data mining and extraction", the conditions and process of implementing and managing data mining in the company; - specifics, possibilities and limits of data mining for a small company; - database marketing and its connection with data-mining in the offline environment - important types of information, their acquisition, analysis and interpretation for marketing decisions; - Data mining in the online environment - what and how to "benefit" from social networks and online marketing; - Web mining - tools for deeper analysis and connection with CRM modules.
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Learning activities and teaching methods
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- Home preparation for classes
- 28 hours per semester
- Participation in classes
- 14 hours per semester
- Term paper
- 18 hours per semester
- Preparation for examination
- 15 hours per semester
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| prerequisite |
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| Knowledge |
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| Prerequisities are not set. |
| Prerequisities are not set. |
| learning outcomes |
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| Knowledge of the concept of data mining |
| Knowledge of the concept of data mining |
| Knowledge of data mining techniques |
| Knowledge of data mining techniques |
| Knowledge of the benefits of data mining |
| Knowledge of the benefits of data mining |
| Knowledge of the most common areas of application of data mining |
| Knowledge of the most common areas of application of data mining |
| Knowledge of data mining efficiency measurement options |
| Knowledge of data mining efficiency measurement options |
| Skills |
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| Explain the principle of data mining |
| Explain the principle of data mining |
| Explain the difference between data mining and other research techniques |
| Explain the difference between data mining and other research techniques |
| Create a data mining usage plan |
| Create a data mining usage plan |
| Design appropriate data mining methods |
| Design appropriate data mining methods |
| Design a way to measure the effectiveness of data mining |
| Design a way to measure the effectiveness of data mining |
| teaching methods |
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| Knowledge |
|---|
| Lecturing |
| Lecturing |
| Dialogic (Discussion, conversation, brainstorming) |
| Dialogic (Discussion, conversation, brainstorming) |
| Skills |
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| Lecturing |
| Lecturing |
| Dialogic (Discussion, conversation, brainstorming) |
| Dialogic (Discussion, conversation, brainstorming) |
| assessment methods |
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| Knowledge |
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| Composite examination (Written part + oral part) |
| Composite examination (Written part + oral part) |
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Recommended literature
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DOSTÁL, Petr. Soft computing v podnikatelství a veřejné správě. Vyd. 1. Brno: Akademické nakladatelství CERM, 2015, 2 sv. ISBN 978-80-7204-896-0..
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EAGLE, Nathan a Kate GREENE. Reality mining: using big data to engineer a better world. 2014. ISBN 9780262529839.
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EAGLE, Nathan. Reality mining : using big data to engineer a better world. MIT Press. c2014.. MIT Press, 2014.
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Han, Jiawei; Kamber, Michelin; Pei Jian. Data mining: concepts and techniques. 3rd ed.. Waltham: Elsevier, 2012. ISBN 978-0-12-381479-1.
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LIU, Bing. Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data. 2nd ed. Springer.2011. ISBN 978-3-642-19459-7..
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Russel, Matthew a. Mining the social web: [analyzing data from Facebook, Twitter, LinkedIn, and other social media sites].. Sebastopol: O'Reilly,, 2011. ISBN 978-1-4493-8834-8.
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