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The Evolution of Analytics and Implications for Industry and Academic Programs

Melissa R. Bowers et al.

INFORMS Journal on Applied Analytics2018https://doi.org/10.1287/inte.2018.0955article
AJG 2ABDC B
Weight
0.51

Abstract

In this work, we discuss how analytics is evolving in industry and academia. To assess industry needs, we conducted a text-mining study of online job postings for analytics-related positions. We also conducted a survey of academic programs in analytics-related master’s programs to ascertain topic coverage relative to industry needs. Based on these two studies, we discuss gaps that we believe need to be addressed. While industry moves along the analytics maturity spectrum from descriptive to predictive to prescriptive optimization-based analytics, analytics master’s programs are focusing less on optimization and more heavily on predictive analytics, thus creating the future potential for a gap in the analytics training provided by academia and the future analytics needs of industry.

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https://doi.org/https://doi.org/10.1287/inte.2018.0955

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@article{melissa2018,
  title        = {{The Evolution of Analytics and Implications for Industry and Academic Programs}},
  author       = {Melissa R. Bowers et al.},
  journal      = {INFORMS Journal on Applied Analytics},
  year         = {2018},
  doi          = {https://doi.org/https://doi.org/10.1287/inte.2018.0955},
}

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The Evolution of Analytics and Implications for Industry and Academic Programs

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Evidence weight

0.51

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.41 × 0.4 = 0.16
M · momentum0.80 × 0.15 = 0.12
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.