Business Intelligence in e-business

Theoretical and practical teaching:  Business intelligence methodology in e-business. Review and analysis of the most important references. Architecture of business intelligence. Data warehouse. ETL processes. Non-relational database. Storages of Big Data. Apache Hadoop. Apache Hive. Methods and algorithms for discovering knowledge in data. Reporting systems. OLAP. Key Performance Indicators. Queries over Big Data. Cloudera tools. Types of applications and tools for business intelligence. The use of the concepts of business intelligence and knowledge discovery for solving problems in e-commerce, e-marketing, e-health, mobile business and other areas of e-business.  Social networks analysis. Analysis of unstructured data. Analysis of multimedia data. Summary of results of current scientific research projects in the field of application of business intelligence in e-business.

The aim of this course is to enable students for independent scientific research and solving actual research problems in the field of knowledge discovery in e-business. Specifically analyzes the concept of knowledge discovery in Big Data in e-business.

1. E-resources from moodle.elab.fon.bg.ac.rs
2. M.Minelli, M.Chambers,A.Dhiraj, Big Data, Big Analytics: Emerging Business Intelligence and Analytic Trends for Today’s Businesses, Wiley, 2013.
3. HC.Chen, RHL.Chiang, VC.Storey, Business Intelligence and Analytics: From Big Data to Big Impact,  MIS Quarterly, Vol.36, No.4, 2012.
4. N.Stefanović, D.Stefanović, B.Radenković, Integrated Supply Chain Intelligence through Collaborative Planning, Analytics and Monitoring in Iraj Mahdavi, Shima Mohebbi, Namjae Cho (Eds.) Electronic Supply Network Coordination in Intelligent and Dynamic Environments Modeling and Implementation (43-92) DOI: 10.4018/978-1-60566-808-6.ch003
5. N.Stefanovic, B.Radenkovic, D.Stefanovic, Designing OLAP Multidimensional Systems For Supply Chain Management, International Journal of Pure and Applied Mathematics, IJPAM, 2007.