Budapest University of Technology and Economics, Faculty of Electrical Engineering and Informatics

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    Databases

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

    Last updated: 2014. november 12.

    Budapest University of Technology and Economics
    Faculty of Electrical Engineering and Informatics

    Software engineering BSc program 

    Course ID Semester Assessment Credit Tantárgyfélév
    VITMA311   3/1/0/v 5  
    3. Course coordinator and department Dr. Gajdos Sándor, Távközlési és Médiainformatikai Tanszék
    4. Instructors Dr. Gajdos, Sándor, Department of Telecommunications and Media-informatics 

     

    5. Required knowledge Basic technical knowledge about programming languages, data structures, algorithms

     

    6. Pre-requisites
    Kötelező:
    (TárgyEredmény( "BMEVISZA213" , "aláírás" , _ ) = -1
    VAGY
    TárgyEredmény( "BMEVIMA2207" , "aláírás" , _ ) = -1
    VAGY
    TárgyEredmény( "BMEVIMA2607" , "aláírás" , _ ) = -1
    VAGY
    TárgyEredmény( "BMEVIMAF509" , "aláírás" , _ ) = -1

    VAGY KépzésLétezik("5N-MGAIN")

    VAGY Training.Code=("5NAA78RESZ")
    VAGY
    EgyenCsoportTagja("Brazil 2015-16-1_erk") )

    ÉS NEM ( TárgyEredmény( "BMEVITMAB00", "jegy" , _ ) >= 2
    VAGY TárgyEredmény("BMEVITMAB00", "FELVETEL", AktualisFelev()) > 0)

    ÉS Training.Code=("5N-A8")

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

    A kötelező előtanulmányi rendek grafikus formában itt láthatók.

    Ajánlott:

    Algorithm theory

    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.

     

    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

       

    • 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

       

    9. Method of instruction

    Interactive lectures in a small group with built-in practices 

    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. Condition for the signature is passing the tests in average. The weakest test result will be ignored.

       

    2. 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. 

       

    11. Recaps Accordig to the Code of Studies and Exams

     

    12. Consultations Individual consultation: upon agreement with the lecturer.

     

    13. References, textbooks and resources 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)

       

    14. Required learning hours and assignment
    Lessons56
    Preparation for lessons28
    Preparation for practices in laboratory20
    Praparation for tests20
    Homework-
    Preparation for exam26
    Total150
    15. Syllabus prepared by
    Name:

     

    Position:

     

    Department:

     

    Dr. Gajdos, Sándor

     

    h. ass. professorDepartment of Telecommunications and Media-informatics