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Introduction to Knowledge Discovery in Data Process in Context of Industry 4.0

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F25840886%3A_____%2F22%3AN0000027" target="_blank" >RIV/25840886:_____/22:N0000027 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.narodacek.cz/wp-content/uploads/2023/01/08_Fridrich.pdf" target="_blank" >https://www.narodacek.cz/wp-content/uploads/2023/01/08_Fridrich.pdf</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Introduction to Knowledge Discovery in Data Process in Context of Industry 4.0

  • Original language description

    This article aims to describe the KDD process, or Knowledge discovery in data, and to present some of the available software tools for this process in connection with Industry 4.0. Methods used to interpret the results in this article include research of professional sources, analysis and synthesis of acquired knowledge, and inductive and deductive approaches. In various branches of the economy, whether it is business economics or macroeconomics, we encounter an ever-increasing amount of generated data. This data can be very useful, as information can be drawn from it, which can then be used to optimize processes that lead to strengthening competitiveness in today's very turbulent market. The more data is created, the more it can cause complications in their identification. Errors also often occur during data generation, due to which the data is not uniform. The results of this work will include a description of the eight important steps of the KDD process.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    50203 - Industrial relations

Result continuities

  • Project

  • Continuities

    N - Vyzkumna aktivita podporovana z neverejnych zdroju

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the International Scientific Conference ECONOMIC POLICY: Post-Pandemic Challenges and Opportunities of the Czech and European Policy

  • ISBN

    978-80-87291-32-0

  • ISSN

    2788-2012

  • e-ISSN

    2788-2020

  • Number of pages

    12

  • Pages from-to

    87-98

  • Publisher name

    Vysoká škola PRIGO

  • Place of publication

    Ostrava

  • Event location

    Čeladná

  • Event date

    Sep 6, 2022

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article