Business Intelligence 2600-MSMz1BI

Lecture:
The lecture offers theoretical foundations that will be useful when using BI systems. Topics:
1. Introduction to BI - a framework for considerations (The times of the information society, Ubiquity of data and Big Data, Review of management information systems)
2. The concept and architecture of BI systems
3. Characteristics of well- and poorly structured problems,
4. Characteristics of the Microsoft Power BI tool
5. Data sources for Business Intelligence
6. Data warehouses
7. ETL operations
8. Power Query
9. Data modeling
10. OLAP
11. Data mining
12. Visualization of results (Reporting and data visualization tools, Dashboards)
13. Applications and development directions of BI systems (BI in management, Business Intelligence policy goals in the organization, Organizing data management processes for BI purposes, BI applications, Development directions of BI systems)

Exercises:
The exercises cover issues related to the use of the Microsoft Power BI tool and the use of BI methods in business analyses. Topics:
1. Introduction to Microsoft Power BI (built-in tools, program interface, overview of possibilities),
2. Data preparation (Power Query, basic data preparation operations, data from different sources, incompatible tables, table decomposition, queries, M language, text analysis)
3. Data modeling (basics of data modeling, Power Pivot, star models, snowflake models, fact constellations, models with staging tables)
4. ETL operations in practice
5. Data visualization (reporting tools, creating dashboards using Power View)
6. Elements of the DAX language
7. Review of semestral projects

Term 2025Z:

Lecture:
1. The lecture provides theoretical foundations intended to be useful for working with BI systems. Topics:
2. Introduction to BI – framework for discussion (the era of the information society, the ubiquity of data and Big Data, overview of management information systems)
3. The concept and architecture of BI systems
4. Characteristics of well-structured and poorly structured problems
5. Characteristics of the Microsoft Power BI tool
6. Data sources for Business Intelligence
7. Data warehouses
8. ETL operations
9. Power Query
10. Data modeling
11. OLAP

12. Data mining
13. Visualization of results (tools for reporting and data visualization, managerial dashboards)
14. Applications and development directions of BI systems (BI in management, objectives of Business Intelligence policy in an organization, organizing data management processes for BI purposes, BI applications, directions of BI system development)

Classes (Practical sessions):
The practical sessions cover topics related to using Microsoft Power BI and applying BI methods in business analysis. Topics:

1. Introduction to using Microsoft Power BI (built-in tools, program interface, overview of capabilities)
2. Data preparation (Power Query, basic data preparation operations, data from various sources, inconsistent tables, table decomposition, queries, M language, text analysis)
3. Data modeling (basics of data modeling, Power Pivot, star schema, snowflake schema, fact constellation schema, models with bridge tables)
4. ETL operations in practice
5. Data visualization (reporting tools, creating managerial dashboards using Power View)
6. Elements of the DAX language\
7. Review of project work

Term 2026Z:

Classes (Practical sessions):
The practical sessions cover topics related to using Microsoft Power BI and applying BI methods in business analysis. Topics:

Type of course

obligatory courses

Mode

Classroom

Learning outcomes

After completing the course, the student:

In terms of knowledge:

• correctly uses terminology related to BI technologies and related technologies such as data mining and data warehouses (K_W01)
• identifies the needs of enterprises related to the use of Business Intelligence technologies (K_W02)
• explains the role of Business Intelligence (BI) technologies in operational and strategic decision-making (K_W05)
• explains concepts such as the information society, the ubiquity of data, Big Data, data warehouses, ETL, OLAP, and data mining (K_W05)
• identifies key elements of Business Intelligence (K_W05)
• indicates the application of information systems and the ubiquity of data in modeling the functioning of organizations (K_W05)
• discusses the functions of the Microsoft Power BI system, including tools such as Power Query, Power Pivot, Power View, and the basics of the DAX language (K_W05)
• analyzes data processing processes, including extraction, transformation, and loading (ETL), and recognizes various data sources and their integration within data warehouses (K_W05)

In terms of skills:

• creates data models using Power Pivot (K_U06)

• visualizes results in order to create managerial dashboards that support decision-making (K_U06)
• processes data using basic knowledge of information and communication technology tools such as ETL, Power Query, Power Pivot, Power View, OLAP, the basics of DAX notation, and data mining in order to create managerial dashboards (K_U06)

• collaborates in a team when preparing data models and the final project (K_U08)
• supports others in the process of preparing the final project (K_U09)

In terms of social competences:

• critically analyzes information using Business Intelligence technology, including Microsoft Power BI, to support operational and strategic decision-making in organizations (K_K01)

Assessment criteria

Learning outcomes will be verified on an ongoing basis through tasks performed by participants during practical classes, a theoretical test, and a semester project.
Graded assessment
No final exam – a single grade for the lecture and practical classes:
• Semester project (50% of the final grade)
• Points obtained during practical classes (30% of the final grade)
• Points obtained during lectures (20% of the final grade)

Bibliography

Literature:
- Microsoft Power BI. Jak modelować i wizualizować dane oraz budować narracje cyfrowe, praca zbiorowa, wyd. III. Wydawnictwo Helion Gliwice 2023.
- Jerzy Surma - Business Intelligence. Systemy wspierania decyzji biznesowych. Wydawnictwo Naukowe PWN, Warszawa 2009.
- Arkadiusz Januszewski – Funkcjonalność informatycznych systemów zarządzania. Tom 2. Systemy Business Intelligence. Wydawnictwo Naukowe PWN, Warszawa 2008.
Additional literature:
- Marco Russo, Alberto Ferrari - Kompletny przewodnik po DAX. Analiza biznesowa przy użyciu Microsoft Power BI, SQL Server Analysis Services i Excel, Wydawnictwo Helion Gliwice 2019.
- Gil Raviv - Power Query w Excelu i Power BI. Zbieranie i przekształcanie danych. Wydawnictwo Helion Gliwice 2020.
- Marco Russo, Alberto Ferrari – Power BI I Power Pivot dla Excela. Analiza danych. Wydawnictwo Helion Gliwice 2020.

Term 2025Z:

Main bibliography:
• Microsoft Power BI. Jak modelować i wizualizować dane oraz budować narracje cyfrowe, praca zbiorowa, wyd. III. Wydawnictwo Helion Gliwice 2023.
• Jerzy Surma - Business Intelligence. Systemy wspierania decyzji biznesowych. Wydawnictwo Naukowe PWN, Warszawa 2009.
• Arkadiusz Januszewski – Funkcjonalność informatycznych systemów zarządzania. Tom 2. Systemy Business Intelligence. Wydawnictwo Naukowe PWN, Warszawa 2008.

Extended bibliography:
• Marco Russo, Alberto Ferrari - Kompletny przewodnik po DAX. Analiza biznesowa przy użyciu Microsoft Power BI, SQL Server Analysis Services i Excel, Wydawnictwo Helion Gliwice 2019.
• Gil Raviv - Power Query w Excelu i Power BI. Zbieranie i przekształcanie danych. Wydawnictwo Helion Gliwice 2020.
• Marco Russo, Alberto Ferrari – Power BI I Power Pivot dla Excela. Analiza danych. Wydawnictwo Helion Gliwice 2020.

Term 2026Z: