Big data wasn’t always “Big Data.”
“I was in the Big Data space before the term was coined. We’d say ‘yeah, there’s a lot of data,’” recalls Bassel Ojjeh, chief executive officer of nPario, a two-year old Palo Alto, Calif.-based firm that sifts through big media corporations’ troves of data to deliver insights about their customers.
Now that we live in a world where devices everywhere are – in his words – “spewing massive volumes of data,” the Big Data brand has caught on.
Today, a whole ecosystem of new businesses is springing up to engage with this new reality – companies that store data; companies that mine data for insight; and, companies that aggregate data to make it manageable.
It brings promise to both big companies that are sitting on storehouses of data and small businesses nimble enough to manipulate them.
But it’s an ecosystem that’s still emerging, and its exact shape has yet to make itself clear.
Looking ahead, here are three things to watch for in this space:
Getting the data will be half the battle
One of the biggest challenges of working with Big Data is assembling it and preparing it for analysis. Part of this problem is technological, but another is old-fashioned organizational wrangling.
“The biggest challenge with big data is organizational,” says Eric Monteiro, a partner at McKinsey & Co. in Toronto.
Corporations that accumulate data storehouses are also, by their nature, inclined to keep it in silos. Corporate divisions are also inclined to keep to themselves and guard their turf; some have their own analytics divisions.
While cross-referencing corporate data with feeds available on the open Web – from Google, for instance – might come naturally to folks in IT, it doesn’t always mesh with the proprietary big-business mindset.
“There’s a wealth of data that they’re just organizationally not prepared to look at,” Mr. Monteiro says.
And then there’s logistics: Different systems store data in different formats, even within the same company. Assembling, standardizing, and cleaning data of irregularities – all without scrubbing it of the information that makes it valuable – is going to be a central challenge of this space.
It will be seamless
The nature of Big Data is taking inhuman amounts of data and distilling it into information that human brains can use. It follows that one fixation in the Big Data space is making the process as seamless as possible for end users.
Startups are aiming to make the process of transferring and sorting through data as simple as prosaic Web apps like filing your taxes online.
“We don’t want to be providing technology for the sake of technology,” Mr. Bassel says. “We want to focus on applications – hide the technology and provide apps for business users.”
For instance, nPario focuses on parsing customer data to paint a detailed picture of what a company’s audience wants, and how best to reach out to individuals.
The company focuses on big business, but Mr. Bassel says that, once easy-to-use services are in place, Big Data techniques can be just as useful for small businesses.
“The winning organization is going to be the organization that leverages data,” he says, even if that organization has 1,000 clients instead of 1 million. “It’s less about volume, and more about having a CEO who says we’re going to be data-driven.”
Insights come where multiple data streams meet
To get a sense of this field’s potential for end users, consider one of the earliest mainstream Big Data products: Google Maps. It’s the quintessential Big Data application, even though it arrived long before the term itself became popular.
Google took a vast storehouse of data that was originally compiled by another company, then put a seamless interface on it, and presented it to a whole new audience.
However, early on, Google made one more critical decision: It opened up Google Maps to third parties, so that anyone could overlay their maps with other data, whether it’s the location of car dealerships or where smartphone users have spotted graffiti in a city.
Google’s decision awoke a generation of users to one of the key lessons of the Big Data era: Well-packaged information is valuable. But some of the most innovative applications will come where enterprising users cross existing data streams, whether public or private.
Whether its geography and retail availability, customer information with public health trends, or the weather. we live in a wild world of information, and the Big Data mindset gives businesses a whole new lens through which to see it.
Special to The Globe and Mail
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