There’s one sure fire way of telling that a technology has crossed the floor from being an intriguing idea to a future giant of IT – and that’s earning a place on Gartner’s Hype Cycle.

This happened with Big Data last year, as Gartner added it to its hype cycle as a ‘technology trigger’ (the first of its five categories) and then moved it this year to its ‘peak of inflated expectations’. This, according to the analyst firm, is a dangerous period for an emerging technology, when its early promise is put to the test in those first tricky implementations that are as likely to fail as succeed. It’s therefore no surprise that the third place in Gartner’s hype cycle is the ‘trough of disillusionment’ and typically the point at which a new technology is loudly trounced as ‘overhyped’.

Big Data, however, has just earned a special place in Gartner’s assessment of the way in which new technologies are conceived, sold and adopted as it has just released a Hype Cycle for Big Data, 2012. This is the first report devoted solely to the topic and, despite the slightly supercilious tone which the media uses to cover new hype cycles, it’s an acknowledgement that Gartner believes big data will go the distance.

What’s more, it also gives a definition to the Big Data market as a group of technologies rather than a homogenous mass. In fact it lists out 47 different big data technologies and terms in an effort to give more definition to a sector where applications can range from inexpensive experiments with cheap servers to Rolls Royce implementations of solutions provided by the likes of SAP or IBM.

Gartner research vice president Hung LeHong acknowledged as much in a recent webinar on the subject, saying, “It’s hard to call big data one single technology. It’s actually a concept, a set of technologies.”

While it’s usually the hype cycle visualization that garners most media attention, Gartner’s researchers have done some really important work to clarify the applications and possibilities of individual big data technologies by writing mini-analyses for the report. By setting the scene for an explosion of big data in such a methodical way, Gartner is playing an important role in giving the sector credibility in the eyes of vendors. So as we enter the next phase of Big Data – namely the point at which the technologies have to face the twin challenges of diversifying and maturing – what’s next?

There will almost inevitably be cynicism, as the companies who either invested in Big Data before they were ready, or picked the wrong solution or partner are forced to abandon projects. We will also see a period of consolidation, as the big software companies go on the acquisition trail to build their portfolios, and natural selection prunes the Big Data start-up ecosystem.

And after that? Plain, old boring maturity: the point at which a technology which is capable of doing remarkable things becomes normal, and useful. Just as email was a miracle twenty years ago, and is now a fact of life, once Big Data has pervaded the organisation it will change it forever, and then we’ll stop noticing it. That’s what Gartner means by the ‘plateau of productivity’.