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Lecturer(s)
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Hub Miloslav, doc. Ing. Ph.D.
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Course content
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Basic concepts of Big Data (BD). Databases, data warehouses and BD. Framework and architecture. Approaches to BD analysis and processing. Methods and tools for storing, managing and analysing BD. BD ecosystem. NoSQL databases. BD development and capabilities.
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming), Skills training
- Home preparation for classes
- 26 hours per semester
- Contact teaching
- 14 hours per semester
- Preparation for an exam
- 50 hours per semester
- Individual project
- 60 hours per semester
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Learning outcomes
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The aim of the course is to introduce students to the issue of working with Big Data, its specifics and tools for its management and analysis.
A student who has successfully completed the course is able to: define basic concepts from the field of BD and use them correctly; describe the structure and basic principles in the design of a database, data warehouse in connection with BD; describe and explain the requirements for data management, metadata and data quality; characterize selected methods and tools for storing, managing and analyzing BD; explain the principles and principles of visualization in the BD environment. A student who has successfully completed the course is able to: implement a system design of the structure of a database or data warehouse depending on the requirements; correctly use basic tools for managing data and metadata; design and implement data visualization depending on the assignment. A student who has successfully completed the course is able to: work in a team and clearly summarize the opinions of other team members; clearly and convincingly communicate information to experts and laypeople about the nature of professional problems and their own opinion on their solution in the field of BD, participate in solving tasks as a member of a team working in the field of BD.
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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
Assigment: completion of the assigned tasks, attendance at the exercises in accordance with the FES regulation; submission of the completed credit project according to the assignment. Examination: written and oral, defence of the final thesis on the assigned topic.
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Recommended literature
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Hendl, J. Big data: věda o datech - základy a aplikace. Praha: Grada Publishing, 2021. ISBN 978-80-271-3031-3.
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Holubová, I., J. Kosek, K. Minařík a D. Novák. Big Data a NoSQL databáze. Praha: Grada, 2015. ISBN 978-80-247-5466-6.
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Kudyba, S. Big Data, Mining and Analytics.. Auerbach, 2014.
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Mayer-Schonberger, V. Big data: Revoluce, která mění způsob, jak žijeme, pracujeme a myslíme.. Praha: Computer Press, 2014.
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Minell, M. Big Analytics.. Wiley, 2013.
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Smolan, Rick. The human face of big data. Sausalito: Against All Odds Productions, 2012. ISBN 978-1-4549-0827-2.
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