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Notorious BIG Data: Don’t Be Fixated On Size

Big Data. What does it really mean? We unpack what Big Data could spell for the apparel industry and explain why bigger isn't always better.

So much has been written about Big Data that it’s not too hard to imagine a day in which Big Data has its own library of big data. One dedicated to capturing and analysing all the words written about Big Data itself. Metadata: The Collected Works.

But amid the whirlpool of words and buzzwords spent documenting the open arms with which the data has been welcomed into industry, something feels left out. And that something leaves us wondering if the term really captures everything we do at EDITD.

Are we Big Data? Sure. We have far more data on the apparel and fashion industries than anyone else in the world. Such a volume that to describe it with the correct reverence, we’d have to use a string of expletives. So much that if we had a penny for every data point – we’d buy France. The entire country. So, beaucoup data.

But more and more, we’ve noticed that when the Notorious Big is trotted out onto the world’s stage, it’s usually, for all its complexity, assessed by a single criterion – its size. The suggestion being that, to use a phrase laden with innuendo, bigger is better.

Even with an industry-leading data set, if we relied on size alone to justify why we’re the best at what we do, we’d be doing it at the expense of the credit due to the ingenuity of all our people who augment and contextualise that data into insight. And that is what feels left out of the Big Data conversation. The entire other half of the industry, the one devoted to the architecture and design that makes the data palatable to the people who need it.

Obviously, insights should absolutely come from a sizeable and credible source of data. But it’s just as important to place equal value on the depth of analysis and who is providing it. Without that second part—which defines what people see, use and rely on—the apparel industry would love us a lot less. We’d basically be offering them spreadsheets. Big spreadsheets. But still.

Big Data: it’s important to place equal value on the depth of analysis and who is providing it.

So, until the perception of what’s being communicated by the phrase “Big Data”, shifts into something more accommodating of its real value and function, we’re going to sit awkwardly with it; as if it were some guy offering chocolates at a bus stop.

Or maybe our response is best summed up by another maxim of grand elocution: it’s not how big it is, it’s how you use it.