Course code DatZ2004

Credit points 3

Database Technologies I

Total Hours in Course81

Number of hours for lectures16

Number of hours for seminars and practical classes16

Independent study hours49

Date of course confirmation06.09.2022

Responsible UnitInstitute of Computer Systems and Data Science

Course developer

author prof.

Gatis Vītols

Dr. sc. ing.

Course abstract

The aim of the study course is to learn data base model creation basics technological implementations.
Studies of basic functionality of database technology are performed. Basics of database design and data models are discussed. Students learn to develop and normalize data tables. Table relationships and basics of data retrieval are learned. Data retrieval from tables with structured query language are discussed and practically applied. Students gain practical knowledge about database management system PostgreSQL and individually develop semester assignment.

Learning outcomes and their assessment

Students gain knowledge about general concepts of database technology and Structured Query Language SQL. Practical skills about the development of databases for storage of various data types, examination of data table design, elimination of design inconsistencies and retrieval of data with Structured Query Language are acquired. Students develop competences of group or individual data analysis, choosing and taking part in discussions about the technological solution for data storage and retrieval.

Course Content(Calendar)

1. Data, information, knowledge (1h lecture).
2. Concept of data model (1h lecture).
3. Relational data model (1h lecture 3 practicals).
4. Normalization of data base structures (1h lecture 1 practicals).
5. Data base management systems (1h lecture 1 practicals).
6. ER model development for particular task (1h lecture 1 practicals).
7. Architecture of data base management system PostgreSQL (1h lecture 1 practicals).
8. Relational data base table development (1h lecture 1 practicals).
9. Data definition language statements (1h lecture 1 practicals).
10. Table relationships (1h lecture 1 practicals).
11. Recursive relationship (1h lecture 1 practicals).
12. Structured query language (1h lecture 1 practicals).
13. Table views (1h lecture 1 practicals).
14. Data retrieval from single table (1h lecture 1 practicals).
15. Data retrieval from multiple tables (1h lecture 1 practicals).
16. Data grouping possibilities in queries (1h lecture 1 practicals).

Requirements for awarding credit points

To receive credit points students must submit and receive positive grade for homework as well as all test average mark must be positive.
1. Development of data base models.
2. Data base model development in data base management system
3. Theoretical test about all topics covered in the lectures.

Description of the organization and tasks of students’ independent work

Students need to individually complete homework which includes development of a data base in database management system, including documentation of the data base.
For development of homework 1 month is given since definition of the assignment.

Criteria for Evaluating Learning Outcomes

Semester final test mark is calculated as an average mark based on student scores gathered from homework and semester tests.
Practicals must be submitted and graded positive.

Compulsory reading

1. Date C.J. Introduction to Database Systems. An 8th Ed. Boston: Addison Wesley, 2004. 1024 p.
2. Coronel C. Database principles: fundamentals of design, implementation, and management. Andover: Cengage Learning, 2013. 866 p.
3. Oppel A. SQL: a beginner’s guide. New York: McGraw-Hill, 2016. 533 p.
4. Kumar V.N.A. PostgreSQL 13 Cookbook. Packt Publishing, 2021. 319 p. (Pieejama Datoru Sistēmu katedras bibliotēkā) (Available at library of Department of Computer Systems)

Further reading

1.Dombrovskaya H., Novikov B., Bailliekova A. PostgreSQL Query Optimization. Apress. 2021. 315 p.

Periodicals and other sources

1.Žurnāls "Data Base Journal". QuinStreet. Pieejams:
2. Emuārs "DB-Enignes Blog", solid IT. Pieejams:


Compulsory course in Computer Science and Computer Science and Information Technology for Sustainable Development.