UPDATED 08:19 EDT / NOVEMBER 12 2013

WANdisco top brass on Big Data disruption | #BigDataNYC

It’s easy to dismiss a disruptive trend as a bubble waiting to burst, yet the reverse holds true for Big Data, according to WANdisco CEO David Richards. The executive stopped by theCUBE with Jagane Sundar, the co-founder and CTO of the company, to detail how analytics are shaking up traditional technology and business perspectives.

Richards believes that organizations seeking to drive value from their data must recognize that Hadoop is more than just a “cheap storage platform,” embrace it, and adapt their legacy applications to fit into the new information paradigm. A growing number of enterprises are doing exactly that, he continues, thanks in large part to the fact that open source software is easier to adopt than proprietary solutions from the likes of Oracle.

Sundar also views Hadoop as a viable enterprise platform, noting that the framework is a scalable and cost-efficient solution for analyzing large volumes of data. He admits that the project currently lacks certain “enablement” features, but stresses that it plays a big part in disrupting the way companies process data.

“Much like we moved to personal computers, this move to clusters of computers running either in the cloud or on-premise is a tectonic shift,” Sundar says. “Do we need this technology? Yes. The data that we are processing is so much more vast, and the fidelity you get from the queries you make is so much better with this volume of data, so the technology is there, the need for the technology is here. I believe that this is truly a tectonic shift.”

Asked about the impact of the mobile explosion on Big Data, Sundar explains that internet users and connected devices are generating more information than ever before. He adds that the low-power ARM chips found in phones and tablets are increasingly making their way into Hadoop clusters as enterprise infrastructure requirements evolve and energy-efficiency moves up the agenda.

Watch the interview below for more in-depth analysis of the Hadoop market.


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