University: Technical University of Košice
Faculty: Faculty of Electrical Engineering and Informatics
Department: Department of Computers and Informatics
Course Number: 26000643 Course Name: Data Processing Technologies and Systems
Type, scope and method of learning activities:
Course Type: Lecture, Laboratory exercise
Recommended scope of the course content (in hours):
Full-time study (hours per week): 2,2
Part-time study (hours per semester): 26,26
Study Method: Attendance
Number of credits: 6
Recommended semester of study: WT
Recommended semester Study programme Study grade Study Method
1.rok WT Cybersecurity (KB_Ing_D_sk)
Informatics (INF_Ing_D_sk)
Informatics (INF_Ing_D_en)
2.rok WT Cybersecurity (KB_Ing_D_sk)
Informatics (INF_Ing_D_sk)
Informatics (INF_Ing_D_en)
Level of study:
Course completion requirements:
Assessment and completion of the course: Credit test and examination
Continuous assessment: Student passes the continuous assessment and receives credits when he or she meets the requirement to obtain at least 21% out of 40%.
Final assessment: Student passes the final assessment and passes the examination when he or she meets the requirement to obtain at least 31% out of 60%.
Overall assessment: Overall assessment is the sum of the assessments obtained by students in the assessment period. The overall result is determined in accordance with the internal regulations of the Technical University in Košice. (Study Regulations, the internal regulation principles of doctoral studies)
Learning outcomes:
The student will gain basic knowledge about alternative database technology: OLTP and OLAP, Data Warehousing; other database technologies - the object and object-relational databases, fuzzy DB, text DB, multimedia DB, deductive DB, main-memory DB, native XML DB; SQL Tuning - Performance Tuning of database server, integration of data sources and application integration; security and databases.
Brief course content:
1. Data Warehouses
2. Operational Systems Data Consolidation, ETL
3. Multi-dimensional modeling
4. The structure of the data warehouse
5. Data Presentation, OLAP analysis
6. The concept of data mining (data mining)
7. Temporal databases
8. Text databases
9. Multimedia databases
10. Safety and databases
11. Virtual Private Database
12. Data Engineering
Recommended Reference Sources:
1. Paulraj Ponniah: Data Warehousing Fundamentals: A Comprehensive Guide for IT Professionals. 2001. John Wiley a Sons, Inc.
2. Ralph Kimball, Margy Ross: The Data Warehouse Toolkit. Second Edition. 2002. Wiley Computer Publishing.
3. W. H. Inmon: Building the Data Warehouse Third Edition. 2002. John Wiley a Sons, Inc.
4. R. Kimball, J. Caserta: The Data Warehouse ETL Toolkit. Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data. 2004, Wiley Publishing, Inc.
5. Kimball, R., Ross, M.: The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, Third Edition. 2013, John Wiley a Sons, Inc.
6. Nagabhushana S.: Data Warehousing. OLAP and Data Mining. New Age International (P) Ltd., Publishers, 2006
7. Zaniolo C: Advanced Database Systems
8. Schutt R., O’Neil C.: Doing Data Science. O’Reilly Media, Inc., 2014
9. Russell Jurney: Agile Data Science. O’Reilly Media, Inc., 2013
Recommended optional program components:
Languages required for the course completion:
Course assessment:
Total number of students assessed: 233
  A B C D E FX  
  17% 24% 21% 19% 11% 9%  
doc. Ing. Ján Genči, PhD.
Last modified: 01.09.2022
Approved by: person(s) responsible for the study program