Database Systems II

  • Credits: 3
  • Ending: Examination
  • Range: 0P + 2C
  • Semester: winter
  • Faculty of Economic Informatics

Teachers

Included in study programs

Economic Informatics

Teaching results

After completion of the course, students should have
Knowledge
A. Become familiar with the Data Warehouse and with OLTP and OLAP technologies.
B. Generate outputs from Oracle database in the form of XML-
Skills
C. Create a program in PL/SQL and PHP.
D. independently debug an existing program in PL/SQL /PHP language (in terms of identifying and removing the cause of the error).
Competencies
E. design and develop a functional application in PL/SQL /PHP/, based on a given assignment.-
F. Create a small information system designed to perform analysis of the economic activity of the enterprise.

Indicative content

Advanced analysis of the economic activity of the enterprise
2. Data analysis - multidimensional analysis
3. Central data warehouses and data marts. Data warehouses in the environments of selected database vendors. Ways of presenting data and information..
4. Data warehouse, essence, terminology. Areas and reasons for data warehouse use.
5. Process of data acquisition into the data warehouse. Transformation mechanism.
6. Data cube and data cube operations
7. Data warehouse creation, data structure in data warehouse, data models in data warehouse
8. Querying, data mining, monitoring and data warehouse administration.
9. OLTP and OLAP technologies. Comparison of data warehouses and relational databases. Methods of creating reports in databases and data warehouse
10. Programming in PL/SQL
11. Using PHP to create the IS application layer
12. Tools for creating web applications
13. Current BI systems

Support literature

1. Reese, J., & Housley, M. (2022). Fundamentals of data engineering: Plan and build robust data systems. O’Reilly Media. ISBN 9781098108304
2. Kleppmann, M. (2017). Designing data-intensive applications: The big ideas behind reliable, scalable, and maintainable systems. O’Reilly Media. ISBN 9781449373320
3. Kimball, R., & Ross, M. (2013). The data warehouse toolkit: The definitive guide to dimensional modeling (3rd ed.). Wiley. ISBN 9781118530801
4. Kultan, J., & Schmidt, P. (2019). Pokročilé využitie databáz pre ekonomické školy: vybrané otázky. Vydavateľstvo EKONÓM. ISBN 978-80-225-4612-6.
5. Schmidt, P., & Bandurič, I. (2015). Úvod do tvorby webu. Ekonóm. ISBN 978-80-225-4209-8.
6. Kultan, J. (2012). Databázové systémy (1. vyd.). Vydavateľstvo EKONÓM. ISBN 978-80-225-3350-8.
7. Laberge, R., et al. (2012). Datové sklady: Agilní metody a business intelligence. Computer Press. ISBN 978-80-251-3729-1.
8. Kislingerová, E. (2010). Manažerské finance (3. vyd.). C. H. Beck. ISBN 978-80-740-0194-9.
9. Závodný, P., Kristová, G., & Praženka, D. (2010). Distribuované spracovanie dát. Vydavateľstvo EKONÓM. ISBN 978-80-225-2901-3.
10. Sedláček, J. (2007). Finanční analýza podniku. Computer Press. ISBN 978-80-802-251-1830-6.

Syllabus

1. Advanced Analysis of Enterprise Economic Activity Course introduction, objectives, and expected learning outcomes. Discussion on business analysis needs in practice. 2. Multidimensional Data Analysis Fundamentals of OLAP, dimensions, metrics, hierarchies. Practical examples of multidimensional modeling. 3. Central Data Warehouses and Data Marts Explanation of warehouse architecture, central DW vs. data marts. Case studies and real systems. 4. Data Warehouse: Essence and Terminology Key terms: ETL, data mart, staging area, metadata. Use-case examples. 5. Data Acquisition and Transformation Mechanism Introduction to the ETL process. Data cleansing and transformation rules. 6. Data Cube and OLAP Operations Building a data cube. Performing OLAP operations: slice, dice, roll-up, drill-down. 7. Designing a Data Warehouse and Data Modeling Star and snowflake schema design. Hands-on warehouse modeling task. 8. Querying, Data Mining, and DW Administration Basic SQL queries for DW. Introduction to data mining. System monitoring in DW. 9. OLTP vs. OLAP, Report Generation Comparison of systems. Creating outputs from relational DBs and data warehouses (Oracle Reports, Power BI). 10. PL/SQL Programming Functions, procedures, packages, triggers. Practical server-side coding. 11. Using PHP in Database Information Systems PHP integration with databases. Form processing and dynamic data display. 12. Tools for Building Web Applications Deployment of apps using HTML, CSS, and PHP. Hands-on project. 13. Current BI Systems Overview of BI tools: Power BI, Tableau, Qlik. Implementation and practice.

Requirements to complete the course

Requirements to complete the course:
40% continuous written work, 20% semester work, 40% exam

Student workload

Total study load (in hours):
Student's workload (for a course that has 4 credits): 104 h (participation in lectures 26 h, participation in seminars 26 h, preparation for seminars 13 h, elaboration of a semester project 13 h, preparation for the exam 26 h)

Language whose command is required to complete the course

slovak

Date of approval: 04.03.2025

Date of the latest change: 06.11.2025