TAILIEUCHUNG - Data warehousing and data mining - a case study

This paper shows design and implementation of data warehouse as well as the use of data mining algorithms for the purpose of knowledge discovery as the basic resource of adequate business decision making process. The project is realized for the needs of Student's Service Department of the Faculty of Organizational Sciences (FOS), University of Belgrade, Serbia and Montenegro. This system represents a good base for analysis and predictions in the following time period for the purpose of quality business decision-making by top management. | Yugoslav Journal of Operations Research 15 (2005), Number 1, 125-145 DATA WAREHOUSING AND DATA MINING - A CASE STUDY Milija SUKNOVIĆ, Milutin ČUPIĆ, Milan MARTIĆ Faculty of Organizational Sciences, University of Belgrade, Belgrade, Serbia and Montenegro Milijas@, Cupic@, Milan@ Darko KRULJ Trizon Group, Belgrade, Serbia and Montenegro KruljD@ Received: August 2004 / Accepted: February 2005 Abstract: This paper shows design and implementation of data warehouse as well as the use of data mining algorithms for the purpose of knowledge discovery as the basic resource of adequate business decision making process. The project is realized for the needs of Student's Service Department of the Faculty of Organizational Sciences (FOS), University of Belgrade, Serbia and Montenegro. This system represents a good base for analysis and predictions in the following time period for the purpose of quality business decision-making by top management. Thus, the first part of the paper shows the steps in designing and development of data warehouse of the mentioned business system. The second part of the paper shows the implementation of data mining algorithms for the purpose of deducting rules, patterns and knowledge as a resource for support in the process of decision making. Keywords: Decision support systems, data mining, data warehouse, MOLAP, regression trees, CART. 1. PREFACE Permanently decreasing ability to react quickly and efficiently to new market trends is caused by increase in competition on the market. Companies become overcrowded with complicated data and if they are able to transform them into useful information, they will have the advantage of being competitive. 126 M. Suknović, M. Čupić, M. Martić, D. Krulj / Data Warehousing and Data Mining It is familiar that the strategic level of decision-making usually does not use business information on a daily basis but instead, cumulative and derivative data .

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