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Fourth Industrial Revolution and Evolution of Data Science: Challenges for Official Statistics

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  • Popoola, Osuolale Peter
  • Adeboye, Olawale Nureni

Abstract

Fourth Industrial Revolution is describes as exponential growth of several key technological fields’ concepts, such as intelligent materials, cloud computing, cyber-physical systems, data exchange, the Internet of things and blockchain technology. At its core, data represents a post-industrial opportunity. The effects of technologies have provided new avenues of data for official statistics, which can then be harnessed through the power of data science. However, as data continue to grow in size and complexity; new algorithms need to be developed so as to learn from diverse data sources. The limitation of conventional statistics in managing and analyzing big data has inspired data analysts to venture into data science. Data Science is a combination of multiple disciplines that use statistics, data analysis, and machine learning to analyze data, and extract knowledge and insights from it. These swathes of new digital data are valuable for official statistics. This paper links industrial eras to the evolution of statistics and data; it examines the emergence of big data and data science, what it means, it benefits and challenges for official statistics

Suggested Citation

  • Popoola, Osuolale Peter & Adeboye, Olawale Nureni, 2023. "Fourth Industrial Revolution and Evolution of Data Science: Challenges for Official Statistics," EconStor Research Reports 268717, ZBW - Leibniz Information Centre for Economics.
    • Handle: RePEc:zbw:esrepo:268717
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    1. Melanie Arntz & Terry Gregory & Ulrich Zierahn, 2016. "The Risk of Automation for Jobs in OECD Countries: A Comparative Analysis," OECD Social, Employment and Migration Working Papers 189, OECD Publishing.
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    More about this item

    Keywords

    Industrial Eras; Data Evolution; Big Data Revolution; Data Science; Official Statistics;
    All these keywords.

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