Power BI
- Ending: Examination
- Range: 0P + 2C
- Semester: summer
- Faculty of Economic Informatics
Teachers
Included in study programs
Teaching results
By completing the course, students will acquire knowledge, skills and competencies that they will be able to use effectively when working with data, creating reports and analyzing them. The learning outcomes contribute to fulfilling the goals of the study program.
After completing the course, students will have:
Knowledge
A. To understand Business Intelligence terminology and its importance for modern business. To know the core components of the Power BI service and use Power BI Desktop.
B. To understand principles of importing data from various sources and the capabilities of Power Query for data cleaning and transformation.
C. To understand the creation of data models, including defining relationships between tables.
D. To know the DAX (Data Analysis Expressions) functions and their use for calculations and analytical expressions.
E. To understand principles of building visualizations and reports, including customization, interactivity, and the use of filters.
Skills
B. To import data from various sources and perform data cleaning and transformation using Power Query.
C. To build and manage data models, including defining and adjusting table relationships.
D. To apply DAX functions to create calculations, measures, and analytical indicators.
E. To create and customize Power BI visuals, add interactive elements, and prepare user-oriented reports.
F. To read, analyse, and interpret data by understanding visuals, key metrics, comparisons, and identifying correlations or potential causal relationships.
Competentness
A. To apply Business Intelligence principles and terminology in data analysis and reporting tasks.
B. To independently handle diverse data sources and perform complete data preparation and transformation.
C. To design, build, and optimize data models for analytical purposes.
D. To use DAX effectively for developing advanced analytical solutions and logical indicators.
E. To present data creatively and effectively through visuals and interactive reports.
F. To independently analyse and interpret results from visualizations and support decision-making in business practice.
Indicative content
1. Introduction and basics:
2. Introducing the Power BI tool and its capabilities.
3. Overview of the main components: PowerBI Desktop, Power Query, and Power Pivot. Working with data:
4. Import methods and data sources.
5. Data transformation for analysis.
6. Creating data models and defining relationships.
7. Data analysis and visualization:
8. Basics of the DAX language and its functions for statistical analysis.
9. Data visualization techniques in Power BI.
10. Reporting and information sharing:
11. Creating and publishing reports.
12. Report sharing and collaboration.
13. Analysis of output data and interactive work with report
Support literature
1. Aspin, A. (2020). Pro Power BI Desktop: Self-service analytics and data visualization for the power user. Apress.
2. Chmelár, M. (2022). Reporting v Power BI, PowerPivot a jazyk DAX. SmartPeople.
3. Microsoft. (n.d.). Dokumentácia k službe Power BI. Microsoft Learn. https://learn.microsoft.com/power-bi
4. Microsoft. (n.d.). Použitie jazyka DAX v aplikácii Power BI Desktop. Microsoft Learn. https://learn.microsoft.com/training/paths/dax-power-bi
5. Microsoft. (n.d.). Rýchly začiatok: Pripojenie údajov v aplikácii Power BI Desktop. Microsoft Learn. https://learn.microsoft.com/power-bi/connect-data/desktop-quickstart-connect-to-data
6. Mehta, B. (2023). Microsoft Power BI Cookbook (3rd ed.). Packt Publishing.
7. Singh, R. (2024). Mastering DAX for Power BI: Advanced data modeling and analytics. O’Reilly Media.
8. White, M. (2022). The Definitive Guide to DAX (2nd ed.). Microsoft Press.
Syllabus
1. Introduction and basics Introduction to the concept of Business Intelligence and the role of analytical tools in modern organizations. Overview of basic analytical workflows and how Power BI fits into the broader BI ecosystem. 2. Introducing the Power BI tool and its capabilities Presentation of Power BI as a comprehensive analytical platform. Explanation of its features, architecture and the types of tasks it is designed to support, including reporting, modelling and data visualization. 3. Overview of the main components: Power BI Desktop, Power Query and Power Pivot Description of the core components used in the report development process. Explanation of their roles — Desktop for modelling and reporting, Power Query for data transformation and Power Pivot for analytical modelling. 4. Import methods and data sources Overview of available data connectors and import options. Explanation of how to work with files, databases, cloud sources and web services. Discussion of best practices for preparing data for analysis. 5. Data transformation for analysis Using Power Query to clean, filter, merge and restructure data. Explanation of key transformation steps required for analytical modelling. Importance of data quality and consistency. 6. Creating data models and defining relationships Design principles for building structured data models. Explanation of relationships, cardinality and cross-filtering. Best practices for creating efficient and logical models. 7. Data analysis and visualization Overview of analytical workflows and the role of DAX in extending model logic. Explanation of how measures and calculated columns influence visual outputs. Introduction to model evaluation. 8. Basics of the DAX language and its functions for statistical analysis Introduction to DAX syntax, data context, row context and filter context. Overview of common functions used for time intelligence, aggregation and statistical evaluation. Practical examples in analytical tasks. 9. Data visualization techniques in Power BI Principles of designing effective visuals and dashboards. Explanation of chart types, formatting tools and usability guidelines. Emphasis on clarity, data storytelling and readability. 10. Reporting and information sharing Steps for creating polished and structured analytical reports. Explanation of report navigation, bookmarks, drill-through and layout optimization. Preparing reports for distribution. 11. Creating and publishing reports Workflow from report development to publishing in the Power BI service. Explanation of dataset refresh, workspace management and security considerations. 12. Report sharing and collaboration Methods of sharing reports within an organization — sharing, apps, and workspaces. Introduction to user permissions, roles, and collaborative features supporting teamwork. 13. Analysis of output data and interactive work with reports Developing the ability to interpret results using visuals, filters, and drill-down interactions. Techniques for identifying trends, deviations, and relationships. Practical analysis scenarios supporting strategic decision-making.
Requirements to complete the course
Continuous solution of tasks during exercises 50%, 51% of this obligation is required for the exam.
The final task verifies the achieved level of practical competences.
Final exam - written form, 50% (passing the exam means obtaining at least 51% of the exam evaluation) The theoretical part verifies the achieved level of theoretical competence results.
Student workload
3 credits x 26 hours= 78 hours
Study load distribution:
Seminar participation: 26 hours
Preparation for seminars: 13 hours
Project preparation: 13 hours
Preparation for the final exam: 26 hours
Language whose command is required to complete the course
Slovak
Date of approval: 04.03.2025
Date of the latest change: 06.11.2025