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Highlights From The 2017 Data Science Survey

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Karl Rexer of Rexer Analytics is at Predictive Analytics World this week (as am I) and he gave some quick highlights from the 2017 Rexer Analytics Data Science Survey. They’ve been doing survey since 2007 (and I have blogged about it regularly) and the 2017 is the 8th survey with 1,123 responses from 91 countries. Full details will be released soon but he highlighted some interesting facts:

  • Formal data science training is important to respondents (75% or so) with particular concerns about data preparation and misinterpreting results when people don’t have formal training.
  • Only about one third have seen problems with DIY analytic and data science tools, which is pretty good and getting better.
  • Most data scientists use multiple tools – an average of 5, still – with SQL, R and Python dominating across the board outside of academia.
  • R has shown rapid growth over the last few years with more usage and more primary usage every year and RStudio is now the dominant environment.
  • While there’s lots of interest in “deep learning”, 2/3 have not used deep learning at all with only 2% using it a lot so it’s not really a thing yet.
  • Job satisfaction is good and most data scientists are confident they could find a new job – not a big surprise.
  • People agree that a wide range of skills are needed with domain knowledge scoring very highly as important. Despite this recognition everyone still wants to learn technical skills first and foremost!

Looking forward to getting the full results.

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