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Data-Mining Opportunities for Small and Medium Enterprises with Official Statistics in the UK

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  • Coleman Shirley Y.

    (Industrial Statistics Research Unit, School of Mathematics and Statistics, Newcastle University, Newcastle upon Tyne, NE1 7RU, United Kingdom of Great Britain and Northern Ireland)

Abstract

There is a growing interest in data amongst small and medium enterprises (SMEs). This article looks at ways in which SMEs can combine their internal company data with open data, such as official statistics, and thereby enhance their business opportunities. Case studies are given as illustrations of the statistical and data-mining methods involved in such integrated data analytics. The article considers the barriers that prevent more SMEs from benefitting in this field and appraises some of the initiatives that are aimed at helping to overcome them. The discussion emphasizes the importance of bringing people together from the business, IT, and statistical worlds and suggests ways for statisticians to make a greater impact.

Suggested Citation

  • Coleman Shirley Y., 2016. "Data-Mining Opportunities for Small and Medium Enterprises with Official Statistics in the UK," Journal of Official Statistics, Sciendo, vol. 32(4), pages 849-865, December.
  • Handle: RePEc:vrs:offsta:v:32:y:2016:i:4:p:849-865:n:6
    DOI: 10.1515/jos-2016-0044
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    References listed on IDEAS

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    1. Sara Fontdecaba & Pere Grima & Lluís Marco & Lourdes Rodero & José Sánchez-Espigares & Ignasi Solé & Xavier Tort-Martorell & Dominique Demessence & Victor Martínez De Pablo & Jordi Zubelzu, 2012. "A Methodology to Model Water Demand based on the Identification of Homogenous Client Segments. Application to the City of Barcelona," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(2), pages 499-516, January.
    2. Ron S. Kenett & Galit Shmueli, 2014. "On information quality," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 177(1), pages 3-38, January.
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