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Why you’ll always need more Data Scientists … and that’s a bad thing
- GFK_of_xmaspast 11y agoThe author is associated with an outfit called Tableau, and here's the takeaway line from the article: "But hardly any one is buying the Tableau service suite. Instead, they are going about the more pricey route to build their own stack in-house." And in that light it's basically a big ad.
- alttab 11y agoIn my mind - this is apples and oranges. Within my organization we have both Tableau, and 5 data scientists. We are operating at a fairly large scale, so Tableau can't handle our data directly. Ultimately, we use our own backend (along with AirBnB Airflow) to generate views that Tableau can handle. I'm not convinced tableau at this point is totally necessary, although the web-UI is arguably better than e-mailing a spreadsheet around. Not sure its worth the additional cost though. Overall, its still too expensive and too hard to manage, analyze and present data analysis. Today if you are doing it at scale it seems you need lots of fancy software and an entire team of smart data people, along with potentially infrastructure engineers to build the pipelining. That's why you are starting to see different types of solutions like hybrid toolsets like DataBlade.io (http://datablade.io/ http://datablade.io/) and vertical turn key analysis like ZIIBRA (http://www.ziibra.com/ http://www.ziibra.com/). I have no affiliation to these companies.