Skip to main navigation menu Skip to main content Skip to site footer

Peer Reviewed Article

Vol. 2 (2015)

Data Science: The Sexiest Job in this Century

Submitted
16 February 2015
Published
30-04-2015

Abstract

Data science is the study of huge amounts of data in order to uncover insights that may be used to assist companies in making strategic decisions. There are several routes to a job in data science; the majority, but not all, entail a little math, a little science, and a great deal of interest in the subject matter of data. New data scientists must be inquisitive, critical, and persuasive in their reasoning. The research focuses on why data science is regarded as the sexiest job in the twenty-first century, as seen by the high compensation paid to qualified people.

References

  1. Cleveland, W. S., & Hafen, R. (2014). Divide and recombine (D&R): Data science for large complex data. Statistical Analysis and Data Mining, 7(6), 425-433. https://dx.doi.org/10.1002/sam.11242
  2. Fox, P., & Hendler, J. (2014). The science of data science. Big Data, 2(2), 68-70. https://dx.doi.org/10.1089/big.2014.0011
  3. Hazen, B. T., Boone, C. A., Ezell, J. D., & Jones-Farmer, L. (2014). Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications. International Journal of Production Economics, 154, 72-80. https://dx.doi.org/10.1016/j.ijpe.2014.04.018
  4. Jifa, G., & Zhang, L. (2014). Some comments on big data and data science. Annals of Data Science, 1(3-4), 283-291. https://dx.doi.org/10.1007/s40745-014-0021-9
  5. Lupia, A., & Elman, C. (2014). Openness in political science: Data access and research transparency: Introduction. PS, Political Science & Politics, 47(1), 19-42. https://dx.doi.org/10.1017/S1049096513001716
  6. Mangilli, A. (2014). From data to science: Planck data and the CMB non-gaussianity. International Astronomical Union.Proceedings of the International Astronomical Union, 10, 131-134. https://dx.doi.org/10.1017/S1743921314013465
  7. Provost, F., & Fawcett, T. (2013). Data science and its relationship to big data and data-driven decision making. Big Data, 1(1), 51-59. https://dx.doi.org/10.1089/big.2013.1508
  8. Reed, D. (2014). Data smart: Using data science to transform information into insight. Journal of Direct, Data and Digital Marketing Practice, 15(4), 354-355. https://dx.doi.org/10.1057/dddmp.2014.33

Similar Articles

1-10 of 27

You may also start an advanced similarity search for this article.