Getting Started With Big Data in the Channel

By Michael Vizard  |  Posted 2014-03-18 Email Print this article Print
 
 
 
 
 
 
 
big data

"Big data" is an abstract term, but it represents a set of technologies with real revenue potential.  Making headway in this space will require patience.

The challenge with big data in terms of actually trying to monetize it is that it is as much a concept as it is a set of technologies that companies in the channel can sell. As a result, it takes a lot of patience on the part of solution providers to get customers to the point where they are buying products and services.

The numbers look promising. In fact, IDC predicts a 31.7 percent growth rate for big data software, hardware and services through 2016. However, IDC also finds that 63 percent of IT and business executives are not familiar with the term "big data" and 68 percent of them don't have any stated business intelligence/analytics goal.

Even organizations that are familiar with the term don't have much in the way of actual big data skills. For solution providers with those skills, there should be significant opportunities—that is, assuming they have the patience and wherewithal to walk customers through all the phases of big data projects spanning months, sometimes years, to complete.

Companies in the channel that have already begun to pursue big data report that one of the biggest challenges they face is all the missionary work that needs to be done before a prospect can be converted into a revenue-producing opportunity.

"There's still a lot of confusion about what big data is," said Bill Dunn, CEO of Dunn Solutions Group, an SAP channel partner. "When you talk to a customer, you get a lot of different interpretations."

Setting Up Hadoop Projects

David Overcash, CTO for Brightlight Consulting, an IBM business partner, said the best approach is to getting customers familiar with big data is to either start a Hadoop project using a cloud service or deploy a small 25-node Hadoop cluster. In fact, Overcash said one of the problems with big data is that the industry has not done a very good job of explaining exactly what the use cases are for big data.

"We've spent the last two years doing a lot of big data education," Overcash said. "We're just starting to come out of the phase now."

As a result, it may take a while yet before Brightlight sees the full return on its big data investments, he said.

In the short term, the priority is getting customers exposed to big data technologies, which is challenging, given the maturity of big data products and technologies, said Tricia Wurts, principal of channel consulting firm Wurts & Associates. "Vendors still have a lot of work to do in terms of making big data something that can be easily consumed by the channel," she said.

When it comes to big data, vendors need to provide a lot of help to partners if they are going to succeed over the long haul, said David Jonker, director of big data for SAP.

"A lot of our focus at SAP is on providing pre-sales support," said Jonker. "Big data is something that evolves little by little over time."

Another key to big data success, said Bruce Weed, program director for big data at IBM, is to make sure the pre-sales effort turns into an actual sale by clearly defining the rules of engagement before the project begins.

"You need to make sure there is a real business case for the project, and you need to make sure you define when the proof of concept stage is going to end," Weed said.

Late last year, IBM began seeking a fair amount of discretionary funding being set aside for big data projects, Weed said. Solution providers should be aware of the fact that those projects span multiple products and technologies that will go way beyond Hadoop. For IBM, that includes everything from real-time streaming analytics to cognitive computing applications based on Watson.

SAP is also pursuing a big data agenda that goes well beyond Hadoop.  SAP's big data strategy ranges from analytics applications in its BusinessObjects portfolio to the SAP HANA in-memory computing platform, Jonker said.

Any combination of those technologies can help create opportunities for solution providers that could easily span the rest of the decade, Jonker said. However, he cautioned: "There is no cookie-cutter approach to big data."

Michael Vizard has been covering IT issues in the enterprise for 25 years as an editor and columnist for publications such as InfoWorld, eWEEK, Baseline, CRN, ComputerWorld and Digital Review.

 
 
 
 
 
 
 
 
 
 

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