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Databases

Adatbázisok
A tantárgyleírás hatályossága
Hatályosság kezdete:
2026. March 21.
Hatályosság vége:
Subject name (Hungarian, English)
Adatbázisok
Databases
Subject code BMEVITMA311
Subject type
Training Level
Course types and hours (weekly/semester)
Course type lecture tutorial laboratory
hours (weekly) 3 1 0
type (linked/independent) derived course
Assessment type vizsga
Credits 5
Subject coordinator
DR. Gajdos Sándor
position: adjunktus
Responsible department
Távközlési és Mesterséges Intelligencia Tanszék
Faculty Villamosmérnöki és Informatikai Kar
Subject website
Primary curriculum type
Direct prerequisites – Strong prerequisite none
Direct prerequisites – Weak prerequisite none
Direct prerequisites – Parallel prerequisite none
Direct prerequisites – Milestone prerequisite none
Direct prerequisites – Exclusion none

Objectives

Programme
  • 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

     

  • Tuple relational calculus, domain relational calculus, safe expressions.

     

  • Functional dependencies, determinant, key, superkey, candidate key

     

  • Armstrong axioms, soundness and completeness, derivation rules

     

  • Normal forms of 0NF, 1NF, 2NF, 3NF, BCNF

     

  • Closure of dependency sets, closure of attribute sets

     

  • Decomposition of relational schemes. Lossless and dependency preserving decompositions. Decomposition in a given normal form.

     

  • Fundamentals of transaction management

     

To make students familiar with the operation and usage of database management systems. Application of the theory also in the engineering practice. 

Learning outcomes

Ez a tantárgy a KKK rendeletben meghatározott, következő kompetenciák fejlesztését szolgálja:

Knowledge

No learning outcomes recorded.

Skills

No learning outcomes recorded.

Attitudes

No learning outcomes recorded.

Autonomy and responsibility

No learning outcomes recorded.

Oktatási módszertan

Interactive lectures in a small group with built-in practices 

Tanulástámogató anyagok

Online források
Recommended books:  ; Ullman: Principles of Database and Knowledge-Base Systems, Comp. Sci. Press vol. I-II, 1990. ; Ullman-Widom: First Course in Database Systems, 2007. ; Ullman: Principles of Database Systems, Comp. Sci. Press 1982. (with recommended excercises) 

Recommended preliminary knowledge for completing the subject

Knowledge type competencies
(azon előzetes ismeretek összessége, amelyek megléte nem kötelező, de a tantárgy eredményes teljesítését nagyban elősegíti)
Basic technical knowledge about programming languages, data structures, algorithms 
Skill type competencies
(azon előzetes képességek és készségek összessége, amelyek megléte nem kötelező, de a tantárgy eredményes teljesítését nagyban elősegíti)
nincs
Recommended (non-compulsory) preliminary competencies
(azon ajánlott (nem kötelező) előzetesen megszerzendő kompetenciák összessége, amelyek jelentősen hozzájárulnak a tantárgy eredményes teljesítéséhez)
Basic technical knowledge about programming languages, data structures, algorithms 
General rules
Requirements: 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. Condition for the signature is passing the tests in average. The weakest test result will be ignored.  In the exam period: Written exam, similar to the problems of the midterm tests. Scoring condition for successful written exam is at least 40%. Below 40% the exam is unsuccessful.   Additional possibilities: Accordig to the Code of Studies and Exams 
Assessment methods
In-term assessments

No detailed assessments provided.

Weight of in-term assessments

No weights provided.

Exam-period assessments

No detailed assessments provided.

Weight of exam elements

No weights provided.

Grade calculation

No grade thresholds provided.

Attendance requirements

No attendance requirements provided.

Rules for retake and resubmission

Not provided.

Short description

Not provided.

Detailed description

Not provided.

Recommended courses
Algorithm theory
Workload to complete the subject

No workload breakdown provided.

Validity of subject requirements
Requirements valid from:
Requirements valid until:
Curriculum placement

No curriculum placements recorded for this subject version.