Home > Business intelligence in e-business-selected chapters

Business intelligence in e-business-selected chapters

Study programE-business and system management
Study groupElectronic business, E-business technologies
Course statusElective
TeachersRadenković Božidar, Despotović-Zrakić Marijana,Bogdanović Zorica, Barać Dušan, Labus Aleksandra,Bojović Živko
Course content

Lectures: Business processes in e-business and the role of business intelligence. Characteristics of business intelligence in B2B and B2C e-commerce. The architecture of business intelligence systems. Cloud infrastructure for business intelligence. Data storage in e-business. Non relational databases. ETL processes. Big data infrastructure and services. Apache Hadoop ecosystem. Systems for reporting and key performance indicators. Methods and algorithms for knowledge discovery in data. Real time reporting and analytics. Overview of open source and commercial solutions for e-business intelligence. Applying the concepts of business intelligence to solve problems in e-commerce, e-marketing, e-government , e-health , mobile business , smart grid management and other areas of e-business. Business intelligence for systems based on Internet of things. Social network analysis. The analysis of unstructured data. Analysis of multimedia. Data visualization.

Practical classes: Apache Hadoop ecosystem. Import and export of relational data into Hadoop. Ad hoc queries using Hive tools. Executing queries using a HiveQL. Queries in real time using Impala. Solving typical problems of data manipulation in e-business in the Hadoop environment: parallel sort, search, analysis of the hyperlinks on the Internet, analysis of log files, personalized advertising on the Internet, analysis of e-mails. The analysis of unstructured data in e-business applications: pattern detection, online market segmentation, consumer behavior analysis,  implementation of real time recommender systems. Social network analysis. Facebook Social Graph API. Twitter API. API of other social media. Apache Storm framework for data processing in real time. Advanced data analysis using Mahout. Data visualization.


The aim of this course is to enable students to independently design, implement and use business intelligence systems in e-business. The specific objective is to enable students to apply the concepts of knowledge discovery in large amounts of data in e-business (big data).

  1. Materials in e-form, on site
  2. B.Radenković, М.Despotović-Zrakić, Z.Bogdanović, D.Barać, А.Labus, Elektronsko poslovanje, FON, 2015.
  3. M.Minelli, M.Chambers,A.Dhiraj, Big Data, Big Analytics: Emerging Business Intelligence and Analytic Trends for Today’s Businesses, Wiley, 2013.
  4. J. Leskovec, A.Rajaraman, J. Ullman, Mining of Massive Datasets, сопствено издање, 2014
  5. HC.Chen, RHL.Chiang, VC.Storey, Business Intelligence and Analytics: From Big Data to Big Impact,  MIS Quarterly, Vol.36, No.4, 2012.
  6. 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

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.