Objectives and competences
Students acquire at this course
1. in-depth understanding of the role and importance of computer databases
2. the ability of independent data modelling with an emphasis on relational and object models
3. in-depth understanding of the architecture of database management systems
4. ability to work independently with data within modern databases
5. the ability to create organizational and personnel elements in the operation of, and the operation of databases themselves
Content (Syllabus outline)
1. Basic terms used with databases
2. Theoretical background
3. Data modelling and database planning (relational and object databases)
4. Database management systems
5. Database architectures
6. Blockchain databases
7. Databases on the web and cloud databases
8. Data-warehouses
9. Online analytical processing
10. NO-SQL databases
11. Big data and real-time analytics
12. Organizational approaches to databases
13. Legal and security issues
14. Contemporary guidelines
Learning and teaching methods
Lectures
Case studies
Exercises
Individual work in groups: developing a database
Intended learning outcomes - knowledge and understanding
Knowledge and understanding:
• to argue the role and importance of computer databases
• to model data in relational and selected NoSql databases
• to assess the suitability of database management systems in a given context
• to build a data model
• to implement a data model in a chosen database management system
• to organize the database life cycle
Intended learning outcomes - transferable/key skills and other attributes
- ability to analyze a system and
- to build and implement a database model in selected database management system;
- ability to organize life cycle of a database
Readings
1. Šet A (2017) Načrtovanje in postavitev podatkovnih baz. Ljubljana, i2.
2. Coronel C, Morris S (2017) Database systems: design, implementation, and management (12. izd.). Boston, MA: Cengage Learning.
3. Kleppmann M (2017) Designing data-intensive applications: the big ideas behind reliable, scalable, and maintainable systems. Sebastopol, CA: O'Reilly Media.
4. Kimball R, Ross M, Becker B, Mundy J, Thornthwaite W (2016) The Kimball group reader: relentlessly practical tools for data warehousing and business intelligence remastered collection (2. izd.). Indianapolis, IN: John Wiley & Sons.
Prerequisits
Prerequisites for enrolling:
in-depth knowledge of the set theory
basic knowledge of ICT
understanding of systems analysis
basic knowledge of computer programming
Exam admission requirement:
positive evaluation of a seminar work and its defence and positive examination of tasks at exercises
Additional information on implementation and assessment Ongoing assessment of knowledge or written exam 100 %
