The Faculty of Maritime Studies and Transport
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Traffic Data Management


Basic content:

  • Supply Chain Data Management
  • Analyzing Data Tools and Approaches
  • Master Data Management concept
  • Big Data – fields/areas of use, models, architecture, analszis of massive data
  • Innovative solutions for logistics and transport data management
  • Artificial Intelligence in logistics and transport
  • Data warehouses, Data mining, Business intelligence
  • Machine learning from data
  • Blockchain technology
  • Security and protection of business data
  • Advanced data management and processing using Excel and Access

Goals and competencies

Students should be aware of information tools and technologies, which are used for management and analysing of massive data resulting from business processes. They should be able to identify the basic characteristics, methods, and examples of applications and reasons for the use of particular form of IT tool or technology designed for these purposes.

During the exercises students should learn the advanced ways of management and processing of large sets of data using tools like Excel and Access.

Basic literature

  1. Jurij Jaklič, Upravljanje in uporaba podatkov, učno gradivo, 2002, UL EF, ISBN 961-6430-29-7.
  2. Kononenko, Igor; Kukar, Matjaž. Machine learning and data mining : introduction to principles and algorithms. Chichester: Horwood Publishing, cop. 2007. ISBN 1-904275-21-4
  3. Frank, Malcolm; Roehrig, Paul; Pring, Ben, What to do when machines do everything: how to get ahead in a world of AI, algorithms, bots, and big data. Hoboken, New Jersey: Wiley, 2017, ISBN 978-1-119-27866-5.