Subject: Introduction to Business Intelligence Systems (12 - IM1038)


Basic Information

CategoryProfessional-applicative
Scientific or art field:Production Systems, Organization and Management
InterdisciplinaryNo
ECTS6
Course specification

Course is active from 01.10.2013..

The goal of the course is to introduce the students to the basic concepts of computer technologies and systems that are used to aid the process of strategic decision making, as well as the principles of data mining, which form the foundation of such systems.
Upon successful completion of the course, students will know the capabilities and limitations of the state-of-the-art business intelligence systems. They will be able to use such systems to aid strategic decision making, efficiently. They will grasp the technologies that form the basis of such systems, the data that is stored in BI systems and information that can be gained through its processing. In addition they will be able to assess the reliability of such information, as well as the forms which it takes.
The course will cover the following areas: basic concepts of business intelligence, management information systems, data bases management systems and data warehouses. Knowledge representations used in data mining, types of data, data acquisition and filtering. Big data visualization, and basic techniques for regression, classification and clustering. Finally, the applications of business intelligence in different domains will be covered. The theoretical instruction will be accompanied by the practical training focused on the use of open-source data mining solution Wakaito Environment for Knowledge Analysis - WEKA.
Lectures and laboratory exercises, test and exam project. The labs will focus on training the students to use the state-of-the-art tools for data mining.
AuthorsNameYearPublisherLanguage
Džejms Veterbe, Efraim MaklinInformaciona tehnologija za menadžment2002Zavod za udžbenikeSerbian language
Dubravko Ćulibrk, Milan MirkovićOsnovi eksploatacije i istraživanja podataka, skripta2012FTN, Novi SadSerbian language
Carlo VercellisBusiness intelligence: data mining and optimization for decision making2009WileyEnglish
Ian H. Witten, Eibe Frank, Mark A. HallData Mining: Practical Machine Learning Tools and Techniques2011Morgan KaufmannEnglish
Course activity Pre-examination ObligationsNumber of points
Project taskYesYes30.00
TestYesYes10.00
Written part of the exam - tasks and theoryNoYes30.00
Lecture attendanceYesYes5.00
Computer exercise attendanceYesYes5.00
Oral part of the examNoYes20.00
Name and surnameForm of classes
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Mirković Milan
Full Professor

Lectures
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Ćulibrk Dubravko
Full Professor

Lectures
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Miković Ivan
Assistant - Master

Computational classes
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Novković Milana
Teaching Associate

Computational classes