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A company full of people great at communication but too little technical expertise will fail. I think it takes both types - technical gurus who can generate useful information and solve the harder problems, plus connectors/communicators who gather information.

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I get the feeling at many companies now, there are fewer truly interesting technical problems than there are engineers enthusiastic or desperate to exercise their hard-won CS knowledge. Most real-world work of commercial value requires skill of course, and experience, but is not especially algorithmic. I think the surge of interest in DS is that here people see an opportunity to do something mathematical day-to-day (but 10% or less of DS is the "sexy" stuff).

Much of the work I do that could be considered "data science" involves trying to write generic visualization tools that allows us to plot various datasets and the results from models we've built (a lot of 2D/3D/4D weather/atmospheric data).

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