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“Tame” the data makers

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I’ve heard of “taming data.” But the week before last at Strata I heard it in a new context: taming behavior.

Taming data has been “nichy,” as fellow TDWI writer Steve Swoyer puts it. He says, “It doubtless explains the etymology of, for example, Tamr.”

But Swoyer pushes on from there, as Swoyer knows how to do.

[Notice the] consonance between to wrangle and to tame. Both are grounded in the same metaphorical frame. Both are grounded in the same metaphor. This pre-conscious framing/understanding of the issue is more interesting than the stupid terms.

Former IBM sales engineer Lamont Lockwood, now the “Integration Expert,” sees two definitions. One is simple: to straighten and calm streaming data. “You don’t have time to fix it later,” he explains. “You need smart models to keep up.”

That leads to Lamont’s second, “nefarious” definition: taming the users who produce the data. “You’ll be trackable every day and every minute,” he muses, “like call-center workers….This is happening.”

Don’t call yourself a “data scientist”

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Someone introduced himself recently as a “data scientist” to a data warehouse pro I know. “I thought he was a fool,” said Interworks consultant Tim Costello. He says it’s a meaningless term — and I believe it’s another one of those distractions thrown around in a roiling industry.

One of the most interesting of the others I’ve heard is Scott Davis, the founder of Lyzasoft. He emailed this week from somewhere on the Caribbean, “Data scientist is just a term someone applied to a set of skills and practices that have existed for a very, very long time. Like, since the invention of the abacus.”

What does he say to those who think it’s an attempt to distinguish between data analysts of any level and those at the top of the discipline? “The attempt is not by someone who does this stuff,” he writes. “It is by someone who is selling something…either a book or a training regimen or a system or a degree or a tool or….”

I looked for Stephen Few’s opinion, and of course he had one. In his 2,500-word blog post “Are you a data scientist?,” he cites interesting articles and poses good arguments, and essentially agrees with Scott and Tim. “There is indeed a science to data sensemaking,” he writes at the end, “but data science by any other name (and there are many) would smell as sweet.”

But why do we care? We do waste a lot of breath on terminology that means little one way or another. But sometimes it does matter — such as in Jill Dyché’s now-famous blog post “Why I wouldn’t have sex with a data scientist.”

Was he too busy, as she originally thought? Or was the poor guy just too full of himself? Whichever, it demonstrates natural selection the way it’s supposed to work.