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Lecturer(s)
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Martínek Petr, Ing.
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Ševčíková Ivana, Doc. Dr. Ing.
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Course content
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Introduction, database technology - analysis of the current state, development trends, data processing methods Principles and tools of Business Intelligence, layers for data analysis - reporting, data warehouse, data mining .. Approaches to creating data warehouses and data marketplaces, business requirements, project plan. Dimensional model - hierarchy of dimensions, division of attributes into dimensions, facts, attributes, definition of types of relations, additivity of facts, definition of query constraints. Problems of data modeling in data warehouses, characteristics of tables of facts and dimensions, transformations between individual models. Data Cube - Another view of dimensional modeling Data warehouse architecture. Metadata for data warehouse management. Design of technical architecture and infrastructure. Data Mining - data mining, introduction, methods. Data pump, extraction process, data transformation and insertion, data cleaning methods. Data quality. User applications, DW management and growth. Data warehouse implementation technology, data warehouse fulfillment. The problem of big data processing - 5V, visualization.
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Learning activities and teaching methods
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Lecture, Practicum
- Preparation for an examination (30-60)
- 40 hours per semester
- Preparation for comprehensive test (10-40)
- 11 hours per semester
- Contact hours
- 65 hours per semester
- Graduate study programme term essay (40-50)
- 40 hours per semester
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| prerequisite |
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| Knowledge |
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| explain the principles of relational databases, data integrity, and basic SQL commands |
| describe the data modeling techniques |
| explain the basic principles of security of data processing |
| Skills |
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| implement and complete an independent project by a specific assignment |
| work as team members with independent responsibility for a specific part of a large system |
| navrhnout databázový systém menšího až středního rozsahu |
| Competences |
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| N/A |
| learning outcomes |
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| Knowledge |
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| describe and explain trends in processing informací |
| explain basic principles of data warehouses |
| orient themselves in the possibilities of database technology with the aim of efficient data processing and knowledge acquisition |
| understand the principle of the Data Pump - the process of extraction, transformation and storage |
| explain and illustrate the methods and models for representation and processing of large and / or unstructured data |
| vysvětlit principy relačních databází, datové integrity a základních SQL příkazů, popsat postupy datového modelování |
| Skills |
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| design and optimize extensive data model |
| select and effectively use methods and technologies for the processing, analysis and representation of large structured and unstructured data |
| Competences |
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| N/A |
| teaching methods |
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| Knowledge |
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| Lecture |
| Practicum |
| Skills |
|---|
| Practicum |
| Competences |
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| Lecture |
| assessment methods |
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| Knowledge |
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| Seminar work |
| Combined exam |
| Project |
| Group presentation at a seminar |
| Skills |
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| Test |
| Seminar work |
| Individual presentation at a seminar |
| Competences |
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| Combined exam |
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Recommended literature
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Krish Krishnan. Data Warehousing in the Age of Big Data - 1st Edition - ISBN: 9780124058910, 9780124059207 View on ScienceDirect Data Warehousing in the Age of Big Data. 2013. ISBN 9780124058910.
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Laberge, Robert. Datové sklady : agilní metody a business intelligence. 1. vyd. Brno : Computer Press, 2012. ISBN 978-80-251-3729-1.
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Meloun M., Militký J. Interaktivní statistická analýza dat. Praha, Karolinum, 2013. ISBN 978-80-246-2173-9.
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Mohammed J. Zaki, Wagner Meira, Jr. Data Mining and Analysis: Fundamental Concepts and Algorithms,. Cambridge, 2014. ISBN 9780521766333.
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Smart Mike. Learn Excel 2013 Expert Skills with the Smart Method. 2013. ISBN 1909253065.
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