Debunking the Top 5 Myths of Big Data

myth with hammer2 300x192 Debunking the Top 5 Myths of Big DataCompanies of all sizes are maneuvering operations to focus on big data to unearth valuable insight from data streaming in from social networks, sensors, mobile devices and the Web.

Even behemoth retailer Wal-Mart has a “maniacal focus” on doing everything it can to leverage the data it collects from 200 million transactions per week to improve the shopping experience of its customers, says CIO Karenann Terrell, speaking at a recent event in Silicon Valley.

The company has also been moving fast to add data scientists to its ranks in its headquarters in California, she adds.

“The number of people who really understand the power of data and how to put it in order is very small,” Terrell says. “It’s a new, emerging area that got hot fast.”

Pacific Gas & Electric’s big data issue comes in the form of handling the reams of data it collects throughout the day by smart meters, notes the utility’s CIO, Karen Austin, speaking at the same event.

To help organizations that are grappling with analyzing the tsunami of data flowing into their networks, Chris Smith, Accenture’s federal chief technology and innovation officer, and former CIO of the U.S. Department of Agriculture, recently debunked the top five myths of big data.

Myth #1
Big Data Can Be Ignored

Some people believe that because their organizations are moving to a cloud model, big data will be the problem of their managed services providers, Smith notes. But moving to the cloud requires organizations to understand the data going into the cloud and to retain a snapshot of the entire data landscape.

Myth #2
Big Data Only Refers To Size

The size of the data deluging many organizations has grown exponentially, but big data is about more than size. It requires organizations to consider the seemingly infinite sources of data and locations, all of which must be accounted for in company processes and technology.

Myth #3
Technology Can Handle Big Data

Advanced analytics will help companies extract actionable insight from data and support the move to predicting outcomes rather than solely reacting to situations. But organizations still need to prepare for making data-driven decisions by hiring the right people. And they need to develop structures for this new way of working.

Myth #4
Government Cannot Learn From The Private Sector

Government data management does differ from the private sector, but agencies can learn from businesses, Smith argues. Industries like financial services and retailing have been pioneers in the big data realm and can be sources of inspiration for agencies.

Myth #5
Big data Can Be Felled By A Silver Bullet

It’s impossible to find one solution to the big data challenge. Instead, organizations “need a suite of tools and platforms, processes and personnel to effectively collect, store, manage and draw insights from this data [and they] must adopt a continuous improvement mindset, where the big data roadmap is continuously reassessed and recalibrated,” Smith notes.

Next steps:

  • Subscribe to our blog to stay up to date on the latest insights and trends in big data.
  • Join us on August 23 at 1 p.m. EDT for our complimentary webcast, “In-Memory Computing: Lifting the Burden of Big Data,” presented by Nathaniel Rowe, Research Analyst, Aberdeen Group and Michael O’Connell, PhD, Sr. Director, Analytics, TIBCO Spotfire. In this webcast, Rowe will discuss recent findings from Aberdeen Group’s December 2011 study on the current state of big data, which shows that organizations that have adopted in-memory computing are not only able to analyze larger amounts of data in less time than their competitors – they do it much, much faster. TIBCO Spotfire’s Michael O’Connell will follow with a discussion of Spotfire’s big data analytics capabilities.
  • Download a copy of the Aberdeen In-Memory Big Data whitepaper here.


Read this post in source website.

No comments yet.

Leave a Reply

Google+