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An approach to big data analytics in construction industry

Author

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  • Miglena Stoyanova

    (University of Economics Varna, Bulgaria)

Abstract

Construction is often considered to be a slow-changing industry. However, construction companies are already collecting vast amounts of data that they can use in a meaningful way to keep up with growing customer demands for complex, fast projects. Now more than ever, companies need to find new ways to structure and analyze data to improve productivity and overall performance, as well as differentiate themselves in the marketplace. The study aims to present the different types of big data, specific to the field of construction, and to develop an approach for performing big data analytics within the construction organizations. It is based on the research of existing specific approaches to the analysis of different types of big data in construction. The proposed approach can be used as a reliable analytical process that can be improved and adapted to the specifics of each construction company. The study is part of Project BG05M2OP001-1.002-0002-C02 Digitalization of Economy in a Big Data Environment.

Suggested Citation

  • 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.
    • Handle: RePEc:kab:journl:y:2022:i:2:p:6-18
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    File URL: https://eknigibg.net/Volume8/Issue2/spisanie-br2-2022_pp.6-18.pdf
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    References listed on IDEAS

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    1. 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.
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