1. SylabUZ
2. Faculty of Engineering and Technical Sciences
3. winter term 2017/2018
4. computer science - Erasmus programme
5. IT systems in business management

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IT systems in business management - course description

Aim of the course

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.

Prerequisites

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Scope

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.

Teaching methods

Lecture, laboratory exercises.

Learning outcomes and methods of theirs verification

Outcome description	Outcome symbols	Methods of verification	The class form

Assignment conditions

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%

Recommended reading

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

Further reading

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

Notes

Modified by dr inż. Anna Pławiak-Mowna, prof. UZ (last modification: 04-05-2017 11:04)