1. SylabUZ
2. Wydział Nauk Inżynieryjno-Technicznych
3. semestr zimowy 2024/2025
4. Biznes elektroniczny - Program Erasmus pierwszego stopnia
5. Data warehouses and reporting services

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Data warehouses and reporting services - opis przedmiotu

Cel przedmiotu

Familiarizing students with the concept of data warehouses and presenting the data lifecycle in a data warehouse. Developing students' skills in designing and implementing data warehouses. Learning methods of creating Business Intelligence type reports using descriptive and exploratory analytics. Developing skills in data visualization for reporting purposes

Wymagania wstępne

Zapisz zmiany

Databases

Zakres tematyczny

Data warehouse architectures. Data lifecycle in data warehouses. Relational and dimensional data models. Analytical queries in SQL. Data cubes. Row-based and column-based databases. Descriptive and exploratory analytics. Self-service Business Intelligence. Reporting using Business Intelligence methods. Management dashboards.

Metody kształcenia

Lecture - conventional lecture using a video projector.
Laboratory - practical exercises in the computer laboratory.
Project - project implementation in a computer laboratory.

 

Efekty uczenia się i metody weryfikacji osiągania efektów uczenia się

Opis efektu	Symbole efektów	Metody weryfikacji	Forma zajęć

Warunki zaliczenia

Lecture - the passing criteria is to obtain positive grades from tests carried out at least once in a semester.

Laboratory - the passing criterion is to obtain positive marks for laboratory exercises and tests.

Project - positive assessment of the project or projects realized during the semester

Final mark components = lecture: 30% + teaching laboratory: 40% + project: 30%

Literatura podstawowa

1. Kimball, R., Ross, M.: The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling (Second Edition), Wiley, 2002
2. Russo M., Ferrari A. Tabular Modeling in Microsoft SQL Server Analysis Services, Microsoft Press, 2017
3. Ferrari A., Russo M. Introducing Microsoft Power BI, Mictrosoft, 2016.
4. Deckler G., Powell B., Mastering Microsoft Power BI - Second Edition: Expert techniques to create interactive insights for effective data analytics and business intelligence, Packt Publlishing, 2022.
5. Deckler G., Learn Power BI - Second Edition: A comprehensive, step-by-step guide for beginners to learn real-world business intelligence, 2022
6. Goldwasser M., Malik U., Johnston B., The Applied SQL Data Analytics Workshop: Develop your practical skills and prepare to become a professional data analyst, 2nd Edition. Wydanie II, Packt Publishing, 2020.
7. SQL Server 2012 Tutorials: Analysis Services - Multidimensional Modeling SQL Server 2012 Books Online, Microsoft, 2012
8. Sarka D., Lah M. Jerkic, Implementing a Data Warehouse with Microsoft SQL Server 2012, O’Reilly, 2012
9. Serra J., Anton B., Reporting with Microsoft SQL Server 2012, Packt Publishing, 2014
10. Inmon W.H.: Building the Data Warehouse, Wiley, 2005
11. Corr L., Stagnitto J.: Agile Data Warehouse Design: Collaborative Dimensional Modeling, from Whiteboard to Star Schema, DecisionOne Press, 2011

Literatura uzupełniająca

Uwagi

Zmodyfikowane przez dr hab. inż. Marek Kowal, prof. UZ (ostatnia modyfikacja: 23-04-2024 15:27)