University of Belgrade, Faculty of organizational sciences

Department for e-business

Big data and business intelligence in e-business

STUDY PROGRAMTEACHERSCOURSE STATUSECTS
Software
engineering and
electronic
business
Zorica M. Bogdanović, Aleksandra B. LabusElective10

The aim of the course

The aim of this course is to enable students to work independently as researchers and solve open research problems in the field of business intelligence and big data analytics in electronic business.


Course outcome

Students are trained for independent development and application of methods and techniques of business intelligence and big data analytics in solving various scientific research problems in e-business.


Course content

Methodology of scientific research in the field of business intelligence and big data analytics in electronic business. Review and analysis of the most important references in relevant journals. Review of the results of current scientific research projects in the field of application of business intelligence and big data analytics in electronic business. Business intelligence system architecture. New computing paradigms for big data and business intelligence, cloud and high performance infrastructures. Big data infrastructure for storing large amounts of data. Nonrelational and NoSQL databases. Big table, key-value and document models for data storage. Cassandara, Redis, MongoDB. ETL processes. Acquisition of data from heterogeneous sources. Streaming data into non-relational databases. OLAP hypercubes. Queries over large amounts of data. Mechanisms for fast search of large amounts of data, mapreduce. Methods, techniques and algorithms of big data analytics. Discovering knowledge in data. Real-time knowledge discovery and decision support systems. Machine learning and artificial intelligence in a big data environment. Big data analytics and blockchain. Data visualization. 3D visualizations. Graphs of knowledge. Complex big data applications in e-commerce, digital marketing, industry, e-health, e-education, e-government. Big data analytics in smart environments and crowdsensing. Big data analytics data from social media. Development of a recommendation system. Analysis of unstructured data. Multimedia data analysis. Development of big data services and business intelligence systems: Apache Hadoop ecosystem, Apache Spark, Python data discovery libraries, TensorFlow. Evaluation of developed solutions. Review of current scientific research projects and preparations for competition for international projects in the field of business intelligence and big data analytics in e-business.

Literature

1. Radenković, M., Lukić, J., Despotović-Zrakić, M., Labus, A., & Bogdanović, Z. (2018). Harnessing business intelligence in smart grids: A case of the electricity market. Computers in Industry, 96, 40-53., DOI: 10.1016 / j.compind.2018.01.006
2. J.Lukic, M.Radenkovic, M.Despotovic-Zrakic, A.Labus, Z.Bogdanovic. A hybrid approach to building a multi-dimensional business intelligence system for electricity grid operators, Utilities Policy. DOI: 10.1016 / j.jup.2016.06.010, 2016, ISSN: 0957-1787
3. Lukić, J., Radenković, M., Despotović-Zrakić, M., Labus, A., & Bogdanović, Z. (2017). Supply chain intelligence for electricity markets: A smart grid perspective. Information Systems Frontiers, 19 (1), 91-107, DOI: 10.1007 / s10796-015-9592-z, 2015, ISSN: 1387-3326
4. Milovanović, S., Bogdanović, Z., Labus, A., Barać, D., & Despotović-Zrakić, M. (2019). An approach to identify user preferences based on social network analysis. Future Generation Computer Systems, 93, 121-129, ISSN 0167-739X, https://doi.org/10.1016/j.future.2018.10.028.
5. J. Šuh, V. Vujin, D. Barać, Z. Bogdanović, B. Radenković, Designing Cloud Infrastructure for Big Data in E-Government, Journal for Universal Excellence, vol. 4, no. 1, pp. A26-A38, Faculty of Organizational Studies in Novo Mesto, Slovenia, 2015.
6. B. Davidović, D. Barać, B. Radenković, Designing a collaborative filtering recommendation system in e-commerce, XVI International Symposium SymOrg 2018, Zlatibor, June 2018
7. N.Stefanovic, B.Radenkovic, D.Stefanovic, Designing OLAP Multidimensional Systems For Supply Chain Management, International Journal of Pure and Applied Mathematics, IJPAM, ISSN 1311-8080, 2007.
8. Materials from the e-learning portal moodle.elab.fon.bg.ac.rs