Business information systems
This course is part of the programme:
Bachelor's programme in Engineering and Management (First Level)
Objectives and competences
The primary goal of this course is to teach students the principles of using information technologies in business.
Students obtain the following competences:
- knowledge of basic concepts from information systems field and basics for understanding methodologies and techniques for developing information systems,
- knowledge of software tools that support individual phases of IS development, like, for example, analysis, design, implementation, testing, etc.
Required prerequisite knowledge from courses Basics of ICT and Electrical engineering.
Content (Syllabus outline)
2. Basic definitions
3. Business information systems (IS)
4. Methodology and technology of IS development
5. SQL basics
6. Modelling business information systems
8. Ethics and security of information systems
9. Decision support and expert systems
10. Basics of data mining in the context of information systems
Intended learning outcomes
Knowledge and understanding:
- Acquired knowledge about basic concepts of using informatics for business
- Familiarity with the basic concepts of systems analysis, design and construction of information systems
- Familiarity with the field of information security
- Lectures with active students’ involvement (explanation, discussion, questions and answers, case studies)
- Individual and group research and project work, seminar assignments
- Individual and group consultations (discussion, additional explanation, handling specific questions)
- Remote collaboration by using modern IT tools
- Curtis, G., Cobham, D.: Business Information Systems: Analysis, Design and Practice. Pearson Education Canada, 2008.
- Reiner, K.R., Prince, B., Cegielski, C.: Introduction to Information Systems: Supporting and Transforming Bussiness, Wiley, 2017.
- Dennis, A., Wixom, B.H., Tegarden, D.: System Analysis and Design: An Object-Oriented Approach, Wiley, 2015
- Power, D.J.: Decision Support, Analytics, and Business Intelligence, Business Expert Press, 2013.
- Beaulieu, A.: Learning SQL, O’Reilly Media, 2009.
Type (examination, oral, coursework, project): examination (50%), project/ seminar work (50%) 50/50
Assist. Prof. Aneta Trajanov, Assist. Prof. in the field of computer sience and informatics, is a researcher at the Department of Knowledge Technologies, JSI, and an assistant professor at the University of Nova Gorica. She completed her PhD on machine learning in 2010 at the Jozef Stefan International Postgraduate School, and a post-doc at Ruđer Boškovič Institute, Zagreb, Croatia in 2015/2016. Her main research interests are machine learning and knowledge discovery from environmental data, decision support, inductive logic programming and equation discovery. She works on several European, as well as national, projects in the area of agroecology, where she applies different machine learning methods for analysing (agro)ecological data.
1. SANDÉN, Taru, TRAJANOV, Aneta, SPIEGEL, Heide, KUZMANOVSKI, Vladimir, SABY, Nicolas, PICAUD, Calypso, HENRIKSEN, Christian B. H., DEBELJAK, Marko. Development of an agricultural primary productivity decision support model: a case study in France. Frontiers in environmental science, ISSN 2296-665X, 2019, vol. 7, str. 58-1-58-13, doi: 10.3389/fenvs.2019.00058. [COBISS.SI-ID 32342311]
2. BAMPA, Francesca, TRAJANOV, Aneta, DEBELJAK, Marko, et al. Harvesting European knowledge on soil functions and land management using multi%criteria decision analysis. Soil use and management, ISSN 0266-0032, 2019, vol. 35, no. 6, spec. iss., str. 6-20, doi: 10.1111/sum.12506. [COBISS.SI-ID 32292903]
3. TRAJANOV, Aneta, KUZMANOVSKI, Vladimir, RÉAL, Benoît, MARKS PERREAU, Jonathan, DŽEROSKI, Sašo, DEBELJAK, Marko. Modeling the risk of water pollution by pesticides from imbalanced data. Environmental science and pollution research international, ISSN 0944-1344. [Print ed.], 2018, vol. 25, no. 19, str. 18781-18792,doi: 10.1007/s11356-018-2099-7.[COBISS.SI-ID 31356967]
4. TRAJANOV, Aneta, SPIEGEL, Heide, DEBELJAK, Marko, SANDÉN, Taru. Using data mining techniques to model primary productivity from international long-term ecological research (ILTER) agricultural experiments in Austria. Regional environmental change, ISSN 1436-3798, [in press] 2018, 15 str., doi: 10.1007/s10113-018-1361-3. [COBISS.SI-ID 31437607]
5. TRAJANOV, Aneta, KUZMANOVSKI, Vladimir, LEPRINCE, Florence, RÉAL, Benoît, DUTERTRE, Alain, MAILLET-MEZERAY, Julie, DŽEROSKI, Sašo, DEBELJAK, Marko. Estimating drainage periods for agricultural fields from measured data : data-mining methodology and a case study (La JailliÈRe, France. Irrigation and drainage : International commission on irrigation and drainage, ISSN 1531-0353. [Print ed.], 2015, vol. 64, no. 5, str. 703-516, doi: 10.1002/ird.1933. [COBISS.SI-ID 28858919]
6. KUZMANOVSKI, Vladimir, TRAJANOV, Aneta, LEPRINCE, Florence, DŽEROSKI, Sašo, DEBELJAK, Marko. Modeling water outflow from tile-drained agricultural fields. Science of the total environment, ISSN 0048-9697, feb. 2015, vol. 505, str. 390-401, doi: 10.1016/j.scitotenv.2014.10.009. [COBISS.SI-ID 28041255]
7. DEBELJAK, Marko, TRAJANOV, Aneta, STOJANOVA, Daniela, LEPRINCE, Florence, DŽEROSKI, Sašo. Using relational decision trees to model out-crossing rates in a multi-field setting. V: JORDÁN, Ferenc (ur.), SCOTTI, Marco (ur.). Proceedigs of the 7th ECEM, European Conference on Ecological Modelling, 30 May – 2 June 2011, Riva el Garda, Italy, (Ecological modelling, ISSN 0304-3800, vol. 245, 2012). Amsterdam: Elsevier. 2012, vol. 245, str. 75-83, doi: 10.1016/j.ecolmodel.2012.04.015. [COBISS.SI-ID 25848103]
8. TRAJANOV, Aneta. Analysis of results of ecological simulation models with machine learning. Informatica : an international journal of computing and informatics, ISSN 0350-5596, jun. 2011, vol. 35, no. 2, str. 285-286. [COBISS.SI-ID 24882471]
9. TRAJANOV, Aneta, TODOROVSKI, Ljupčo, DEBELJAK, Marko, DŽEROSKI, Sašo. Modelling the outcrossing between genetically modified and conventional maize with equation discovery. Ecological modelling, ISSN 0304-3800. [Print ed.], 2009, vol. 220, no. 8, str. 1063-1072. [COBISS.SI-ID 22574375]
10. TRAJANOV, Aneta, VENS, Celine, COLBACH, Nathalie, DEBELJAK, Marko, DŽEROSKI, Sašo. The feasibility of co-existence between conventional and genetically modified crops : using machine learning to analyse the output of simulation models. V: Proceedings of ICEM 2006, International Conference on Ecological Modelling, Mamaguchi, Japan : 28 August – 1 September 2006, Yamaguchi University, Japan, (Ecological modeling, ISSN 0304-3800, Vol. 215, no. 1/3, 2008). Amsterdam: Elsevier Scientific Publ. Co. 2008, issues 1-3, vol. 215, str. 262-271, doi: 10.1016/j.ecolmodel.2008.02.031. [COBISS.SI-ID 21667367]
University course code: 1GI015
Year of study: 2
- Lectures: 60 hours
- Exercises: 30 hours
- Individual work: 85 hours
Course type: mandatory
Learning and teaching methods:
• lectures with active students' involvement (explanation, discussion, questions and answers, case studies) • individual and group research and project work, seminar assignments • individual and group consultations (discussion, additional explanation, handling specific questions) • remote collaboration by using modern it tools