How easy does Hadoop need to become to penetrate the market fully? As easy as dragging-and-dropping, said Xplenty, a new big data company that aims to allow anyone to use Hadoop in the cloud or on-premise with zero coding knowledge.

Xplenty's chief goal is make it possible "to integrate, process, and prepare data for analytics both on the cloud and on-premise, without any Hadoop expertise or background writing code," it said, adding that "Xplenty users do not need to know how to use Hadoop to use the platform, making data processing accessible for everyone in an organization."

This week, the company announced its first major adoption milestone, reporting that its platform has been used to process a half-million "Hadoop-facilitated data jobs" that account for a perabyte of total data. In a statement, Xplenty CEO and co-founder Yaniv Mor attributed that achievement to the growing popularity of Hadoop generally, as well as to Xplenty's ability to allow organizations to overcome "challenges related to personnel" that result from a shortage of Hadoop talent.

Whether demand for Hadoop engineers will continue to outstrip supply as the big data world matures remains to be seen, and some observers might question whether a code-free big data strategy can be as effective as one that leverages big data processing interfaces in their full complexity. (Disclosure: I'm a guy who still uses bash terminals on a daily basis, so I may be a bit biased toward textual interfaces.)

Still, Xplenty's platform—which is available on Google (GOOG) Cloud Platform, Amazon Web Services (AWS), Rackspace (RAX), and IBM (IBM) SoftLayer—is notable as one of the most extreme examples yet of the effort to make Hadoop easy to use, which is necessary to achieve widespread adoption of next-generation big data technology. And with its recent success securing $3 million in series A funding from Waarde Capital, the company may be on to something.