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Are You Ready for Big Data?

One industry analyst is already predicting that Big Data will be Time magazine's 2013 "Person of the Year." Watching what Google, Amazon, and Facebook have done with Big Data is impressive, enviable.

But what about companies with smaller staffs and budgets? When does it make sense to start up a Big Data program? If your email marketing system isn't talking to your sales force automation system, and neither is synched up with your online purchase system, are you really ready to tackle a Big Data project?

The answer may surprise you as we examine Big Data and its impact on the next generation digital experience in this ongoing series, "Are You Ready for Big Data?"

What is Big Data?

At its most basic, Big Data is simply more data, and more varieties of data, than can be handled by a conventional database. But the term also refers to the many tools and techniques that have emerged to help users mine valuable information from these massive torrents of data. So it's not just the accumulation of information, it's the ability to analyze it for profit, insight, or both.

Many of these new tools have also lowered the cost of mining data. Open source software, like Hadoop, and the availability of cloud services have dramatically lowered the price of a ticket to the Big Data Big Top. Big Data analysis has also been democratized both because large data, and data and machine learning tools, are often available for free.

And fueling this revolution, of course, is the unprecedented amount of information that is now available for analysis and action: every Facebook post or "like," every beep of a supermarket scanner, every blink of a medical device can now be be sorted and analyzed, potentially yielding significant and valuable information. The ability to mine valuable information from these kinds of information torrents—looking for connections that are not obvious—is Big Data.

Still, like some other recent tech terms ("the cloud"), there is some fuzziness to the definition of Big Data. One common approach is to break it down into three "V’s":

  • Volume: Billions of computers, smartphones users, and objects are now operating and interacting with each other, generating exabytes (trust me, that's big) of data every day.
  • Variety: Much of this data is "unstructured," meaning that it doesn't notch neatly into a standard relational database. Unstructured data is a book review on Amazon, a comment on a blog, a video on YouTube, a podcast, a tweet.
  • Velocity: A smartphone user's location data is changing constantly, so is the value of a portfolio held by a customer of an online financial service. These kinds of rapid updates present new challenges to information systems.

Recently Mike Gualtieri, a principal analyst with Forrester Research in Cambridge, Mass. (and the analyst who believes that Big Data will get Time's year-end honor), has come up with what he believes is a "more pragmatic" definition of Big Data, one that he claims is "an actionable, complete definition for IT and business professionals."

Here’s how Gualtieri defines it: "Big Data is the frontier of a firm’s ability to store, process, and access all the data it needs to operate effectively, make decisions, reduce risks, and serve customers."

photo of Mike Gualtieri
Mike Gualtieri,
Forrester Research

Gualtieri says that the key to his definition can be summed up in the acronym "SPA," which stands for: Store, Process, and Access. He advises clients to ask themselves these three questions to determine whether they are able to wring value from a Big Data project:

  • Store: Can you capture and store the data?
  • Process: Can you cleanse, enrich, and analyze the data?
  • Access: Can you retrieve, search, integrate, and visualize the data?

Gualtieri's point is that businesses should define their Big Data projects not by the size or shape of the data, but by what they can accomplish—what they can do—with large, various, and fast-moving data.

The two definitions frame the issue. The three V’s describe what Big Data is in terms of size: how big is it, what it looks like. Gualtieri's definition describes what a company should expect to do with a Big Data project.

Editor’s Note: This is the first post in the ongoing series “Are You Ready for Big Data?” by DC Denison, journalist and former Technology Editor for The Boston Globe.

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