1. SylabUZ
2. Wydział Informatyki, Elektrotechniki i Automatyki
3. semestr zimowy 2022/2023
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 a data warehouse and presenting the data life cycle in a data warehouse. Shaping students' skills in designing and implementing a data warehouse. Learning methods of creating Business Intelligence reports using complex analytical queries and multidimensional analysis. Developing data visualization skills for the needs of reports.

Wymagania wstępne

Zapisz zmiany

Databases

Zakres tematyczny

Data warehouse architecture. Data life cycle in data warehouses. Dimensional data model. Data cubes. Row and column databases. Analytical queries. Multidimensional data analysis and 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. Powell B., Mastering Microsoft Power BI: Expert techniques for effective data analytics and business intelligence, Packt Publishing, 2018
5. SQL Server 2012 Tutorials: Analysis Services - Multidimensional Modeling SQL Server 2012 Books Online, Microsoft, 2012
6. Sarka D., Lah M. Jerkic, Implementing a Data Warehouse with Microsoft SQL Server 2012, O’Reilly, 2012
7. Serra J., Anton B., Reporting with Microsoft SQL Server 2012, Packt Publishing, 2014
8. Inmon W.H.: Building the Data Warehouse, Wiley, 2005
9. 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: 29-04-2022 19:38)