As such, they are sometimes also called bards." And why should you care what a griot is? Because Last.fm recently advertised the position of "data griot" and Chris Heathcote wrote a very smart blog post about it, which is well worth your attention. (The best way to find it is just to Google "data griot".)
As Mr Heathcote pointed out, "griot" catches the eye because it's an unusual term, but it's not an entirely unexpected idea - companies have always needed people to uncover and recount their stories. Previously, they've been called researchers, futurists or consultants but they've tended to do the same thing - investigate the narratives and user-stories around a company, its customers and its products. For a typical packaged goods company, many of these stories, much of this data, would have to be ferreted out first - through market research and customer surveys. For web businesses (and, increasingly, every business is a web business), the data comes for free, a sweeping tide of information that you can't contain; the challenge is not to gather it but to make sense of it.
And perhaps even to go beyond that, perhaps to do more than make sense, perhaps to make drama. The real challenge is to turn it into something people will understand, believe and care about. That's why "griot" is an interesting term. It shakes the shaping of data loose of its associations with science, rigour and spreadsheets and puts it firmly in the world of storytelling and drama.
And we should care about that because data is increasingly a media tool. It's not just something we generate or gather: it's a language we have to talk in, an implement we have to wield. Real people are increasingly aware of the data they create, interact with and own. Businesses are similarly starting to understand the value of data they previously thought of as a by-product. But very few corporations, or individuals, are good at extracting the meaning from, and usefully sharing, all these numbers.
As specialists in analysis and communications, we should be leading the way - blending statistics with design, story-telling with behavioural economics, data-mining with marketing. We should be building the apps that let people aggregate their data and understand their actions. We should be thinking about how to nudge that behaviour through data-stories. Hal Varian, the chief economist of Google, said this about 18 months ago: "The ability to take data - to be able to understand it, to process it, to extract value from it, to visualise it, to communicate it: that's going to be a hugely important skill in the next decades ..." Who are we to argue?