• Be it article or editorial, it's still a good summarization of the "third wave" so to speak of the database world. Right now the role of the data scientist is pretty specialized, but businesses are looking for ways to obtain that function without necessarily hiring someone with the academic credentials. They're looking for tools that enable employees who may not have all the formal training of a data scientist to perform data analysis. Imagine something akin to BIDS that can create flows for data analysis.

    This is both a good and bad thing. It opens up more career opportunities for people who have a knack for analyzing data who may have little to no interest in being a full-fledged DBA. On the other hand, there are fundamentals of statistics and the associated inferential process (to say nothing of good data management) that simply must be understood to analyze data correctly. It isn't terribly difficult to calculate a standard deviation, a confidence interval or a p-value (in fact R makes them pathetically easy), but you really can't evaluate your results without a firm understanding of what those values are telling you about your data.

    In addition to Phil's excellent comments, I would also suggest that even database professionals who aren't necessairly involved in the analysis end of things should at minimum be conversant with these fundamentals not only just to understand what the heck the data whiz-kid is talking about, but also to be able to better design and administer the back-end data systems needed for analysis.

    I, too, look forward to the additional material on this subject.

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    Just my $0.02 from over here in the cheap seats of the peanut gallery - please adjust for inflation and/or your local currency.