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Prototype model for big data predictive analysis in logistics area with Apache Kudu

Author

Listed:
  • Liliya Mileva

    (University of Economics Varna, Bulgaria)

  • Pavel Petrov

    (University of Economics Varna, Bulgaria)

  • Plamen Yankov

    (University of Economics Varna, Bulgaria)

  • Julian Vasilev

    (University of Economics Varna, Bulgaria)

  • Stefka Petrova

    (University of Economics Varna, Bulgaria)

Abstract

Logistics is area, which is evolving rapidly, generating a lot of data lately. There are several problems that, even when partially digitized, require additional work. At the same time there is a need of big data analyses. These analyses are represented by machine learning and statistical analyses. One important problem is these with missing data for delivery in the whole process of transportation, other is about empty freight transportation. The purpose of this paper is to present an ICT prototype model with analytical tool Apache Kudu in logistics area, which will contribute to resolve such problems in area. Content analysis and systematic approach are used. Statistical methods and statistical data are used. Growth rates of empty road transport are calculated. The presented data are for Bulgaria and its neighbour’s county, excluding Romania, because of the missing data. Croatia is also included in the analysis. Growth rate analysis indicates problems with empty fright transport in some countries. The tendency for Bulgaria is to reduce empty road freight transport, even though it is better for logistics organizations to work for optimizing the process of delivery.

Suggested Citation

  • Liliya Mileva & Pavel Petrov & Plamen Yankov & Julian Vasilev & Stefka Petrova, 2021. "Prototype model for big data predictive analysis in logistics area with Apache Kudu," Economics and computer science, Publishing house "Knowledge and business" Varna, issue 1, pages 20-41.
    • Handle: RePEc:kab:journl:y:2021:i:1:p:20-41
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    Cited by:

    1. Radka Nacheva & Maciej Czaplewski, 2024. "Artificial Intelligence In Helping People With Disabilities: Opportunities And Challenges," HR and Technologies, Creative Space Association, issue 1, pages 102-124.
    2. Radka Nacheva & Jose Paulo da Costa, 2024. "Digital Accessibility Needs for People with Disabilities in Higher Education," HR and Technologies, Creative Space Association, issue 1, pages 88-101.
    3. Miglena Stoyanova, 2022. "An approach to big data analytics in construction industry," Economics and computer science, Publishing house "Knowledge and business" Varna, issue 2, pages 6-18.

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