The People of the Petabyte

The earnest editorial staff here at Forbes urge us contributors not to get too clever with headlines, but since headline wit is one of the few genuine and unadulterated pleasures of blogging, I occasionally (okay, often) succumb to temptation and sacrifice SEO best practices for a bit of a private chuckle.

Besides, being at a major data-related conference like Strata, and listening to data geeks salivating over prospects of ruling the world by 2015 using large scale automated analysis of Web content, I’ve realized that it is up to us bad punners, over-clever reference droppers and metaphor-mixers to prevent the data geeks from accidentally creating Skynet.  Or at least delay the takeover. Giving up a few ounces of SEO juice and some traffic is a small price to pay. Call it the Skynet Resistance Tax.

Speaking of data geeks, that’s the topic of this post. I’ve spent much of my first couple of days at Strata idly observing them (and wondering whether I am one of them), and speculating about the various species in the data scene (people-watching is how you stay awake between the interesting slides at conferences).  So here is my informal taxonomy and anthropological survey of data-land.

A Taxonomy for Data Land

The taxonomy part is simple. Apparently the list of species in data land is very short. It has only one item:

• Data scientist

Okay, I am exaggerating a bit, but that’s what it feels like, to hear the talks and hallway conversations. IT admins, six sigma types rushing to the data bandwagon, ex-BI types,  visualization and infographic geeks, analytics geeks, programmers, old-school statisticians, Hadoop wranglers — they all seem to be calling themselves data scientist now. There are more complicated taxonomies floating around, but everybody appears wary of accepting them.

Which brings us to the informal anthropology of what’s going on.

Everybody is a Data Scientist

I was gratified to learn in an early talk during the first day that I am apparently not a newbie to the field at all, like I thought. I too am a  data scientist, and a grizzled veteran at that. Apparently, I am among the vast numbers of people who’ve been doing data science all along without realizing it. All it takes is some rudimentary experience running statistical tests on a data set, mucking around trying to prove a couple of hypotheses, and generating a few visualizations. You don’t need to know that Hadoop is a toy elephant to qualify for the title apparently. Having used Google Analytics or Search Insights counts as having experience with Big Data.

I am not making that case. One of the Strata speakers who can genuinely lay claim to the title made the case.

Extremely generous and inclusive, you say? Therein lies a story.

If you’ve been in the technology world for a while and have surfed a couple of hype cycles, you are probably familiar with all the types of identity angst you encounter around any new technology trend. At any given technology conference, you will find the following types:

• People with chips on their shoulders about being marginalized by the new trend.
• Long-ignored people who suddenly find that they’ve turned into stars, blinking in the spotlight.
• People who feel under-appreciated and powerless.
• People who cannot believe how much power they suddenly have.
• People who secretly feel like fakes and are feeling either gleeful or ashamed about it.
• People who are cleverly switching out their titles from the last hyped fad for the closest one they can find in the new one.
• People upset that other people are taking credit for their old wine by putting it into new bottles.
• Older people insisting nothing has changed (read: “therefore I am still the expert”).
• Younger people insisting everything has changed (read “the old fogeys know nothing; hire me instead”).
• People excited by anything new and shiny, whether or not the understand it.
• Jaded people on paid-for junkets.
• Uber-sociable types for whom it is all one big party.

All in all, every technology trend is a seething drama of identity angst.  And besides individuals, corporations have a stake in the labels-and-titles game as well. Big and established players like IBM, Microsoft and EMC must contend with an endless army of feisty startups trying to redefine the game in their own interests. Multi-million dollar deals can be won or lost based on whether you use the term “Big Data” or “Data Warehousing” in your sales pitch.

What makes the data scene interesting is that this soul-searching for identity appears to be happening with a peculiar urgency, and the data community has reached a certain bizarre consensus position that I’ve never seen before in technology: they’ve decided that everybody is a data scientist. I’ve never seen quite this level of title ambiguity before (the one field that might potentially have more title ambiguity is “user experience”). It’s like the South Park episode about the alien race that uses the word “marklar” for everything