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Critical success factors in big data projects

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24310%2F20%3A00007789" target="_blank" >RIV/46747885:24310/20:00007789 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Critical success factors in big data projects

  • Original language description

    The amount of data grows exponentially every year. Organisations are aware of the wealth contained in this data and continue to make greater investments into Big Data technologies as a result. Such investments are intensive in terms of the time required and financing involved, and often do not achieve the expected results. Many Big Data projects result in failure when the project itself is not finished or is completed with significant deficiencies. The root cause of such a high level of failure remains unclear. A large number of critical success factors have been defined for Big Data projects, but these have failed to increase the success rate substantially. The purpose of this paper is to identify those key critical success factors that currently exist and that may be considered critical and not just important. The research is carried out through a questionnaire survey and semi-structured interviews with respondents who have many years of Big Data experience. A total of five basic critical success factors for Big Data projects were identified.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2020

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    IDIMT 2020: Digitalized Economy, Society and Information Management - 28th Interdisciplinary Information Management Talks

  • ISBN

    978-3-99062-958-1

  • ISSN

  • e-ISSN

  • Number of pages

    8

  • Pages from-to

    459-466

  • Publisher name

    TRAUNER Verlag Buchservice GmbH

  • Place of publication

    Linz, Austria

  • Event location

    Kutná Hora, Czech Republic

  • Event date

    Jan 1, 2020

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article