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Data learning from big data

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  • Torrecilla, José L.
  • Romo, Juan

Abstract

Technology is generating a huge and growing availability of observations of diverse nature. This big data is placing data learning as a central scientific discipline. It includes collection, storage, preprocessing, visualization and, essentially, statistical analysis of enormous batches of data. In this paper, we discuss the role of statistics regarding some of the issues raised by big data in this new paradigm and also propose the name of data learning to describe all the activities that allow to obtain relevant knowledge from this new source of information.

Suggested Citation

  • Torrecilla, José L. & Romo, Juan, 2018. "Data learning from big data," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 15-19.
    • Handle: RePEc:eee:stapro:v:136:y:2018:i:c:p:15-19
    DOI: 10.1016/j.spl.2018.02.038
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    References listed on IDEAS

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    1. Clifford Lynch, 2008. "How do your data grow?," Nature, Nature, vol. 455(7209), pages 28-29, September.
    2. Secchi, Piercesare, 2018. "On the role of statistics in the era of big data: A call for a debate," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 10-14.
    3. James, Gareth M., 2018. "Statistics within business in the era of big data," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 155-159.
    4. Gad Abraham & Michael Inouye, 2014. "Fast Principal Component Analysis of Large-Scale Genome-Wide Data," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-5, April.
    5. Dunson, David B., 2018. "Statistics in the big data era: Failures of the machine," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 4-9.
    6. Vieu, Philippe, 2018. "On dimension reduction models for functional data," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 134-138.
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    Cited by:

    1. Sim Jia Jin & Abdul Halim Abdullah & Mahani Mokhtar & Umar Haiyat Abdul Kohar, 2022. "The Potential of Big Data Application in Mathematics Education in Malaysia," Sustainability, MDPI, vol. 14(21), pages 1-23, October.
    2. Russell Tatenda Munodawafa & Satirenjit Kaur Johl, 2019. "Big Data Analytics Capabilities and Eco-Innovation: A Study of Energy Companies," Sustainability, MDPI, vol. 11(15), pages 1-21, August.
    3. Pedro Galeano & Daniel Peña, 2019. "Data science, big data and statistics," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(2), pages 289-329, June.

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