Course detail
Databases for Process Control
FSI-VDC Acad. year: 2026/2027 Winter semester
The course is an introduction to database systems.
Data processing, redundancy and inconsistency, integrity, confidentiality, multi-user access to data. Index-sequential data organization. Integrity constraints for relationships.
Database system architecture, data models. E-R model, relational algebra, query language of relational algebra.
Theoretical aspects of information systems design. Functional dependencies, normal forms of relations, decomposition theorem.
SQL query language.
Data security.
Clouds and grids.
NoSQL databases.
MongoDB. ElasticSearch. Redis/Valkey.
Supervisor
Department
Learning outcomes of the course unit
Prerequisites
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
Language of instruction
Czech
Aims
Specification of controlled education, way of implementation and compensation for absences
The study programmes with the given course
Programme B-MAI-P: Mathematical Engineering, Bachelor's
branch ---: no specialisation, 6 credits, compulsory-optional
Programme B-STR-P: Engineering, Bachelor's
branch AIŘ: Applied Computer Science and Control, 6 credits, compulsory
Type of course unit
Lecture
26 hours, optionally
Syllabus
1. Definition of the subject, study literature. Database paradigm. Data classification (physical classification, index files). Disadvantages of classical file processing. Database systems, DDL and DML languages. Database system architecture. Physical and logical independence. Data models – relation to JSON and XML.
2. Relational algebra, basic operations, relational algebra as a query language. T-SQL statements – SELECT.
3. Design of data structures. Normal forms of relations. Index. Aggregation functions. Composite aggregation key.
4. SQL. Subqueries. Multiple openings of the same table, 1:N sessions within the same table, examples of use. Nested aggregation, query implementation by SQL query sequences.
5. SQL. Counting with NULL value. Expression of existential and universal quantifier in SQL. Cross query. Action queries. Definitional queries.
6. No-SQL databases.
7. MongoDB. BSON. JSON.
8. Key-Value database. Redis/Valkey.
9. Key-Value database. Redis/Valkey.
10. No-scheme database – ElasticSearch.
11. No-scheme database – ElasticSearch.
12. Graph databases – Neo4j.
13. Implementation models for using multiple database types by application type
Computer-assisted exercise
26 hours, compulsory
Syllabus
1. The most commonly used approaches to working with databases and their software implementation, including the use of Entity Framework.
2. Integration of a database source into a REST application and its correct implementation.
3. Ensuring data validity and consistency in terms of application implementation and design.
4. Use of database procedures, advanced querying techniques, and optimization of data access.
5. Options for integrating and combining multiple database sources in a single application.
6. Strategies for modifying, managing, and updating database structures and data.
7. – 8. Implementation of NoSQL databases and their use for storing unstructured data.
9. – 10. Implementation of in-memory databases for working with data streams and high-speed data processing.
11.–12. Practical examples of the implementation and use of ElasticSearch and Neo4j technologies.
13. Project consultations and individual solutions to implementation problems.