Business Intelligence 2600-MSMdz1BI
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
Course coordinators
Type of course
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
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.