SubjectsSubjects(version: 877)
Course, academic year 2020/2021
  
Database Systems - S445003
Title: Database Systems
Guaranteed by: Department of Computing and Control Engineering (445)
Actual: from 2012
Semester: winter
Points: winter s.:5
E-Credits: winter s.:5
Examination process: winter s.:
Hours per week, examination: winter s.:1/3 Ex [hours/week]
Capacity: unknown / unknown (unknown)
Min. number of students: unlimited
Language: English
Teaching methods: full-time
Level:  
For type:  
Guarantor: Vovsík Jaroslav Ing. Ph.D.
Annotation
Last update: Vovsík Jaroslav Ing. Ph.D. (28.05.2012)
The objective of this course is to make students familiar with the programming in Structured Query Language - a language for database systems - and with the design of databases using relation data model by data normalisation. Students will acquire experience with the most popular database server for back-end of web applications - MySQL - also with three different kind of clients.
Literature
Last update: Vovsík Jaroslav Ing. Ph.D. (28.05.2012)

[1] MySQL 5.1 Reference Manual. MySQL AB & Sun Microsystems, 2009.

[2] Ponniah, P. Database Design and Development: An Essential Guide for IT Professionals. Wiley, Hoboken, New Jersey, 2003.

[3] Wilton, P. and Colby, J. W. Beginning SQL. Wiley, Indianapolis, Indiana, 2005.

Syllabus
Last update: Vovsík Jaroslav Ing. Ph.D. (28.05.2012)

1. Modern database systems, database management systems, basic database system concepts.

2. Basic database operations. Joining of tables, projection, selection, set operations.

3. SQL query language. Queries and commands.

4. Simple queries. Sorting. Limit clause. Union operator. In-line functions.

5. Row selection. Logical operators, regular expressions, predicates.

6. Row grouping. Aggregate calculations. Selection after grouping.

7. Subqueries.

8. Joining of tables.

9. SQL data definition language. Creating, modifying, removing and indexing of tables. Data types.

10. SQL data manipulation language. Adding, updating and deleting of rows.

11. Relational data model. Data integrity. Keys.

12. Data normalisation. Fundamental and higher normal forms.

13. Transactions and their properties. States of transactions. Recovery from failures.

14. Sample queries for data processing. Pivot tables, lists, order, running and sliding averages.

 
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