A tantárgy neve magyarul / Name of the subject in Hungarian: Adatbázisok

Last updated: 2018. május 21.

Budapest University of Technology and Economics
Faculty of Electrical Engineering and Informatics
Course ID Semester Assessment Credit Tantárgyfélév
VITMA004   2/0/3/v 5  
3. Course coordinator and department Dr. Gajdos Sándor,
4. Instructors Dr. Gajdos, Sándor, Department of Telecommunications and Media-informatics
5. Required knowledge Basic technical knowledge about programming languages, data structures
6. Pre-requisites
(NEM (Training.Code=("5N-A8")
VAGY Training.Code=("5N-M8") )

(TargyEredmeny( "BMEVIAUA069" , "jegy" , _ ) >= 2 VAGY
TargyEredmeny( "BMEVIAUA002" , "jegy" , _ ) >= 2 ) )

VAGY Training.Code=("5N-MGAIN")

A fenti forma a Neptun sajátja, ezen technikai okokból nem változtattunk.

A kötelező előtanulmányi rendek grafikus formában itt láthatók.

7. Objectives, learning outcomes and obtained knowledge To make students familiar with the operation and usage of database management systems. Application of the theory also in the engineering practice focusing on relational systems.
8. Synopsis
  • Data and information, structured, non-structured and semistructured data
  • Database management systems, components, operation
  • Data Definition Language, Data Manipulation Language, Host language
  • Layered model of DBMS, principle of data independence
  • Data models, data modelling.
  • Entity-relationship model/diagram, attributes, relationship-types, constraints, specialization, weak entity sets.
  • Relational data model, relational algebra
  • Design of relational schemes from E/R diagram
  • Physical data organization: heap, hash, indexing (sparse, dense) (flat, multilevel)
  • Tuple relational calculus, domain relational calculus, safe expressions.
  • Functional dependencies, key, superkey, candidate key
  • Normal forms of 0NF, 1NF, 2NF, 3NF, BCNF
  • Fundamentals of transaction management
Laboratory synopsis:
  • Getting to know a relational database management system
  • Definition of relational schemes in SQL
  • Database queries in SQL
  • Manipulation of data in SQL
  • XML-based data management

9. Method of instruction

Interactive lectures in a small group with built-in practices. 

The laboratories are scheduled biweekly. Individual preparation is needed for the labs from the specific materials provided by the tutor, then consultation, working on the predefined tasks in the computer laboratory of the university under the supervision of the tutor. The students may finish their tasks and the laboratory report at home as well.

10. Assessment
  1. In the teaching period: 5-6 midterm tests, similar to real, numerical engineering problems. Scoring: from 1 to 5, 1 is the weakest grading. In case of any serious or fundamental mistake, the grading will be 1.
  2. Laboratory: each laboratory practice must be completed at least on passed level.The laboratory practices will be graded based on the a) preparation of the student b) activity during the lab c) quality of the laboratory report.

  3. Condition for the signature is passing the tests in average and all of the laboratory practices must be satisfactory at least.


  4. In the exam's period: written exam, similar to the problems of the midterm tests. Scoring condition for successful exam is at least 40%. Below 40% the exam is unsuccessful. Calculation of the final grade: 30% Laboratory average + 70% written exam.
11. Recaps

Accordig to the Code of Studies and Exams.

Only one laboratory practice can be repeated during the semester if the student failed or missed the lab. 

12. Consultations Individual consultation: upon agreement with the lecturer.
13. References, textbooks and resources Recommended books:
  • Silberschatz, H. F. Korth, S. Sudarshan: Database System Concepts, 6th Edition, 2010.
  • Ullman: Principles of Database and Knowledge-Base Systems, Comp. Sci. Press vol. I-II, 1990.
  • Ullman-Widom: First Course in Database Systems, 2007.
For the labs:
  • Syllabi provided by the tutor
  • Web pages identified by the tutor
14. Required learning hours and assignment
Kontakt óra 56
Félévközi készülés órákra 10
Felkészülés zárthelyire 14
Házi feladat elkészítése 16
Kijelölt írásos tananyag elsajátítása 14
Vizsgafelkészülés 40
15. Syllabus prepared by Dr. Gajdos, Sándor,