A $50 Billion Ego? Big Data Backs Up the Hype

Big Data’s become a victim of the buzz machine, but there’s a reason for the hype.  Few movements have touched so many parts of our economy, impacting the way we do business, communicate and learn.  And there’s big money being thrown at Big Data technology, especially in the past two years.  Exploratory methods have turned into ready business tactics, pumping in even more cash.

Just how much cash are we talking? The total Big Data market reached $11.4 billion in 2012, according to a Wikibon report published this morning.  And factory revenue saw a 59 percent jump from 2011, beating Wikibon’s earlier forecast.  Growing interest has pushed revenue for Big Data-related hardware, software and services in 2012, as a burgeoning industry begins to flex its muscles.  And for good reason.  Wikibon expects the Big Data market to exceed $47 billion by 2017.

Why the Big Boost in Big Data Spending?

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So why the sudden boost in Big Data spending, particularly in the enterprise?  Wikibon attributes the growth to a combination of better understanding of Big Data use cases, and a more mature product line up that’s gaining appeal beyond the early adopters.  We’ve evolved small, proof-of-concept projects to large-scale deployments, landing $100+ deals from government and commercial buyers alike.

Now, some of those smaller, proof-of-concept projects came from some pretty powerful players, like Google and Facebook.  Early supporters of Big Data platforms like Hadoop, these tech powerhouses have spurred a community around data-driven reform, validating an ecosystem in the making.  Even as Big Data requires a retooling at the infrastructure level, the investment is proving well worth it for many in the enterprise.

Big Data Still Faces Challenges

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That’s not to say Big Data doesn’t face obstacles as it strives for the $50 billion mark.  Wikibon warns that Big Data is still an early market, going on to note the challenges ahead, starting with the lack of skilled workers.

The Big Data market is well within the confines of the early adopter phase, poised for significant growth. For the Big Data market to reach its full potential, however, enterprises and vendors alike must overcome a number of obstacles. While a detailed discussion of these obstacles is outside the purview of this report, they are worth noting. They include:

  • The well-publicized lack of analytic specialists and Data Scientists armed with both the technical skill and business acumen to derive insights from large, multi-structured data sets merged from disparate sources;
  • A lack of understanding among enterprises on how to organize Big Data staff to best identify business requirements for Big Data projects, and effectively communicate insights gleaned from Big Data to the business;
  • Organizational resistance to adopting Big Data analytics-driven decision-making in replace of “gut instinct”-style decision-making.

Top Players in Big Data [2012]

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So who’s in line for a piece of Big Data’s $50 billion pie?  In this case, the early bird gets the worm.  Companies like IBM that have cultivated ongoing research around Big Data deployments have had the jump start on products.  According to Wikibon, IBM had the broadest Big Data portfolio in 2012, while HP achieved second place in the overall market for revenue.    Services led the charge for HP’s Big Data revenue, succeeding as a lure for Services-related hardware sales.

In fact, Professional Services makes up the majority of the Big Data market.  Firms like Accenture make up 100 percent of their revenue from Big Data Services, accounting for 39 percent of the market overall.

Big Data has also offset a war between Amazon and Google.  Here is where Amazon is aggressively targeting the enterprise with analytics data layers, and Google plays catch up with the public release of BigQuery, and other developments like MapR as a service via Google Compute Engine.  Microsoft, too, had a 2012 milestone after announcing support for Hadoop.

Great Expectations for Big Data in 2013

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So what can we expect for Big Data in 2013?  A 37 percent growth rate, which will catapult the market to nearly $50 billion in 2017.  And in the spirit of properly employing the bounty of Big Data, its costs will drop as efficiency rises in demand and deployment.  Wikibon anticipates the commoditization of Big Data components will drive the shift towards efficiency, saying,

“Big Data infrastructure, middleware and technical services will become increasingly commoditized as they mature and common standards are adopted.  Practitioners will increasingly look to NoSQL and in-memory database software, streaming analytic platforms, vertically focused analytical and transactional applications and application development platforms (both on-premise and cloud-based) and associated consulting and professional services to address specific, high-value business problems and opportunities.”

While Big Data vendor revenue is forecast to grow significantly over the next five years, Wikibon believes that Big Data practitioners will create significantly more value than technology and service providers in the long-term. When selecting Big Data vendors, it’s critical for CIOs and Big Data practitioners to evaluate the products and services on offer in the context of how best to monetize Big Data to achieve competitive advantage. This includes evaluating “speeds and feeds” and other product features, but should also include evaluating how well vendors can assist enterprises in adopting a sustainable culture of data-driven decision-making.

Read Wikibon’s full report here.

photo credit: krazydad / jbum via photopin cc

About Kristen Nicole

Named by Forbes as a top influencer in Big Data, Kristen Nicole is currently a Senior Editor at SiliconANGLE.com. She got her start with 606tech, a Chicago blog she dedicated to the social media space, going on to become the lead writer and Field Editor at Mashable. Kristen Nicole has also contributed to other publications, from TIME Techland to Forbes. Her work has been syndicated across a number of media outlets, including The New York Times, and MSNBC. Kristen Nicole published her first book, The Twitter Survival Guide, and is currently completing her second book on predictive analytics. Follow my work (and some sprinklings of personal interests) on Google+