Publikation:

What Does It Take to be a Successful Data Scientist?

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Berthold_2-1rfm475k4cgkg9.pdf
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2019

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http://nbn-resolving.de/urn:nbn:de:bsz:352-2-1rfm475k4cgkg9
DOI (zitierfähiger Link)
https://doi.org/10.1162/99608f92.e0eaabfc
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CC BY 4.0

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Open Access-Veröffentlichung
Open Access Gold

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Informatik und Informationswissenschaft: Publikationen
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Published

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Harvard Data Science Review. MIT Press. 2019, 1(2). eISSN 2644-2353. Available under: doi: 10.1162/99608f92.e0eaabfc

Zusammenfassung

Given recent claims that data science can be fully automated or made accessible to nondata scientists through easy-to-use tools, I describe different types of data science roles within an organization. I then provide a view on the required skill sets of successful data scientists and how they can be obtained, concluding that data science requires both a profound understanding of the underlying methods as well as exhaustive experience gained from real-world data science projects. Despite some easy wins in specific areas using automation or easy-to-use tools, successful data science projects still require education and training.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
004 Informatik

Schlagwörter

data science, analytics, practitioner, education, insights, discovery

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ISO 690BERTHOLD, Michael R., 2019. What Does It Take to be a Successful Data Scientist?. In: Harvard Data Science Review. MIT Press. 2019, 1(2). eISSN 2644-2353. Available under: doi: 10.1162/99608f92.e0eaabfc
BibTex
@article{Berthold2019-11-01Succe-47982,
  year={2019},
  doi={10.1162/99608f92.e0eaabfc},
  title={What Does It Take to be a Successful Data Scientist?},
  number={2},
  volume={1},
  journal={Harvard Data Science Review},
  author={Berthold, Michael R.}
}
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