1. SylabUZ
2. Wydział Matematyki, Informatyki i Ekonometrii
3. semestr zimowy 2023/2024
4. Computer science and econometrics - drugiego stopnia z tyt. magistra
5. Data Warehouse

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Data Warehouse - opis przedmiotu

Cel przedmiotu

Present the theory of data warehouse design, learn tools for building queries and reports, and intelligent data analysis.

Wymagania wstępne

Zapisz zmiany

Information technology, Database.

Zakres tematyczny

Lecture

1. Introduction to data warehousing (definitions and terminology).
2. Data warehouse architecture (conceptual, logical and physical model).
3. Data warehouse design (multidimensional models and OLAP operations).
4. Data modeling for data warehouses (point modeling).
5. Physical implementation of the data warehouse (extraction, transformation and loading).
6. Data warehouse systems (review of typical solutions).

Laboratory

1. Introduction to IBM Cognos Insight (browsing and exploring data, creating a data cube).
2. Importing data (guided import and data refresh).
3. Data restructuring (analyzing and calculating data, highlighting exceptions and adding calculations).
4. Creating visualizations (chart review).
5. Construction of the workspace (designing an attractive report).
6. Entering and formatting data (creating a purchasing plan).

Metody kształcenia

Traditional lecture. Laboratory exercises in the computer lab according to prepared instructions.

Efekty uczenia się i metody weryfikacji osiągania efektów uczenia się

Opis efektu	Symbole efektów	Metody weryfikacji	Forma zajęć

Warunki zaliczenia

1. Checking the degree of students' preparation and their activity during laboratory exercises.
2. Obtaining positive grades for all laboratory exercises planned for implementation as part of the laboratory program.
3. A written test to pass the lecture, consisting of questions and tasks verifying knowledge of the material covered.
4. The grade for the course consists of the grade for laboratory exercises (50%) and the grade for the lecture (50%).

Literatura podstawowa

1. William Harvey Inmon Building the Data Warehouse 4th Edition Wiley 2005
2. Ralph Kimball, Margy Ross The Data Warehouse Toolkit: The Defi nitive Guide to Dimensional Modeling, Third Edition Wiley 2013
3. P8175 Student Guide IBM Cognos Insight: Analyze and Share Data Published April 2012

Literatura uzupełniająca

1. Chris Todman Designing a Data Warehouses: Supporting Customer Relationship Management 1st Edition Prentice Hall 2001
2. Ramez Elmasri, Shamkant B. Navathe Fundamentals of Database Systems 7th Edition Pearson 2015

Uwagi

Zmodyfikowane przez dr Ewa Synówka (ostatnia modyfikacja: 29-04-2024 19:36)