1. SylabUZ
2. Wydział Informatyki, Elektrotechniki i Automatyki
3. semestr zimowy 2017/2018
4. Informatyka - Program Erasmus
5. IT systems in business management

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IT systems in business management - opis przedmiotu

Cel przedmiotu

Familiarize students with the principles of the ERP systems and methods of implementation of such systems in the enterprise.

Development of skills in planning and building analytical systems.

Familiarize students with the methods of business data mining.

Wymagania wstępne

Zapisz zmiany

Zakres tematyczny

Enterprise resource planning systems: ERP architectures, Characterization of functional modules of ERP systems, Best business practices for ERP systems, ERP implementation methodologies. Overview and characteristics of popular ERP systems.

Analytical systems: Data sources, Data integration, Overview and characteristics of typical data transformation operations, Design and implementation of data transformation processes, Gathering data in a data warehouse, Multidimensional data structures, Presentation of the results of the analysis in the form of reports.

Data mining: Data cleaning, Outlier detection and handling missing data, Discovering association rules and sequences using Apriori and Frequent Pattern Growth, Generalized Sequential Pattern and PrefixSpan algorithms, Data clustering using hierarchical and iterative optimization algorithms, Data classification using knearest neighbor, decision trees and naive Bayes classifier, Time series analysis using parametric models, Overview of systems for data mining.

Metody kształcenia

Lecture, laboratory exercises.

Efekty uczenia się i metody weryfikacji osiągania efektów uczenia się

Opis efektu	Symbole efektów	Metody weryfikacji	Forma zajęć

Warunki zaliczenia

Lecture – the passing condition is to obtain a positive mark from the final test.

Laboratory – the passing condition is to obtain positive marks from all laboratory exercises to be planned during the semester.

Calculation of the final grade: lecture 50% + laboratory 50%

Literatura podstawowa

1. Kimball R., Ross M.: The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling, Wiley, 2013.
2. Magal S. R., Word J.: Integrated Business Processes with ERP Systems, Wiley, 2011.
3. Wagner B., Monk E.: Enterprise Resource Planning, Cengage Learning EMEA, 2008.
4. Witten I. H., Frank E., Hall M. A.: Data Mining: Practical Machine Learning Tools and Techniques, Morgan Kaufmann, 2011
5. Kimball R., Caserta J.: The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data, Wiley, 2004.
6. Corr L., Stagnitto J.: Agile Data Warehouse Design: Collaborative Dimensional Modeling, from Whiteboard to Star Schema, DecisionOne Press, 2011

Literatura uzupełniająca

1. Meer K.: Best Practices in ERP Software Applications: Accounting, Supply Chain Planning, Procurement, Inventory, iUniverse, 2005.
2. Bradford M.:Modern ERP: Select, Implement & Use Today's Advanced Business Systems, lulu.com, 2008.
3. Han J., Kamber M.: Data Mining: Concepts and Techniques, Morgan Kaufmann, 2011

Uwagi

Zmodyfikowane przez dr inż. Anna Pławiak-Mowna, prof. UZ (ostatnia modyfikacja: 04-05-2017 11:04)