There is no lack of big data software tools nowadays, but businesses often spend much time learning to wield them with little profit to show for it. Could new big data as a service offerings make lighter work of monetization?

“There are a plethora of tools, and tools are good. Platforms are better,” said John Furrier (@furrier) (pictured, center), co-host of theCUBE, SiliconANGLE Media’s mobile livestreaming studio. Furrier and co-hosts James Kobielus (@jameskobielus) (pictured, right) and Peter Burris (@plburris) (pictured, left) read the progress bar on big data Tuesday during theCUBE’s BigData NYC event in New York City. 

The heap of tools that chip away at some portion of the big data problem is too messy and varied for most companies to get their arms around. A platform that synthesizes useful tools into something digestible would be easier to manage. And some big data vendors are trying. But perfecting a one-size-fits-all platform is challenging, since both technologists and businesses are still guessing about how to monetize data in the first place.

One hopeful omen at BigData NYC is “the emergence of a common language about how we think about the characteristics of the problem,” Burris said. This common language will branch out and evolve into unique dialects as individual businesses begin to develop their own big data specialties. And individuals within the same company have their own areas of expertise, which may require targeted data software.

“There’s multiple personas in a company now,” Furrier said. “You have an analytics person, a chief data officer. You might have an IT person; you might have a cloud person.” It may also be difficult to get everyone to agree on a particular toolset, he added.

As-a-service shortcut

The easiest solution for all may not be tools or platforms, but easily consumable services, according to Burris.

“Many of the companies that are in the big data space today that are the most successful are companies that are positioning themselves as a service,” he said. These include software as a service, or SaaS, applications for big data analysis, pipeline management, etc.

Taking implementation details off users’ hands opens up creative elbow room that leads to profitable business insights and ideas, Kobielus pointed out. “You then, as a user, become laser-focused on … ‘There’a bunch of things that this can do for me. I don’t care how it works, really. You — SaaS provider — you worry about that stuff. I can worry now about somehow extracting value,'” Kobielus concluded.

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of BigData NYC 2017.

Photo: SiliconANGLE