Business Intelligence and The Hype Cycle – What it means for “big data.”

Posted on September 3rd 2013

What is “Big Data,” really?

The term “big data” has been thrown around a lot over the last few years. But what is it really? Although there is some debate over the specifics, the most well-known definition has to do with “The 3 Vs.” Coined by Gartner’s Doug Laney (over 12 years ago), the three Vs are: Volume, Velocity, and Variety. Essentially, big data is the concept that businesses are dealing with dramatically increasing amounts of data (volume), faster data generation/delivery (velocity), and data coming from more and more sources (variety) than ever before. The off-shoot of this, now part of the generally understood definition, is that somewhere within these mass collections of data are valuable insights for businesses; insights that can be used to improve operations and effectively increase bottom lines.

But that seems to make sense, so why the “hype?”

The issue with big data is not that it is a made-up concept or even that it’s necessarily misunderstood. Where the dreaded “hype” comes in actually has to do with the businesses that produce solutions to solely deal with big data and the organizations that jump to buy those solutions.

The truth of the matter is, big data is not new. Ever since the beginning of the digital age and the ability of companies to collect data from multiple sources, there has been a need for solutions to help manage that data. When the term “big data” became popular, however, the market experienced a surge of start-up and big name companies capitalizing on the “hype” and vying to become the provider who could best handle big data. Early adopters jumped on the proverbial bandwagon and eventually big data solutions became the must-have for modern business.

Ok, so what does “The Hype Cycle” have to say about big data?

If you haven’t heard of research house Gartner’s “The Hype Cycle” before, you’re not alone. In technology and research circles, however, it has become fairly prominent and is considered a reliable tool for predicting the life cycle of any given “hyped” technology. We won’t delve into specifics here, but do take a minute to look over the hype cycle chart below.

Image from Gartner.com: http://blogs.gartner.com/svetlana-sicular/big-data-is-falling-into-the-trough-of-disillusionment/

According to some industry experts, big data solutions are beginning to lead into the “Trough of Disillusionment” phase of the cycle. Essentially what this means is that at the beginning, these new technologies came onto the market promising all kinds of benefits; some realistic, some not. At its peak, or “The Peak of Inflated Expectations,” businesses were expecting the world from these new technologies and willing to take risks and spend money acquiring them. Now that these solutions have been around a while, however, unrealistic expectations have left businesses disillusioned, and the reality of what big data solutions can and cannot provide is beginning to be realized. According to the Hype Cycle, then, the big data hype is on a downward slope. Businesses will begin to spend less money on these solutions and be more weary of the promised benefits.

So the point is…?

All of this essentially goes to show that with any technology “hype,” the initial boom of interest and investment doesn’t last forever. The lesson to take away from this is that businesses, especially SMBs with a more limited budget and less ability to take risks, should be aware that the next “big thing” isn’t always the best thing. There is something to be said for the tried-and-true, and sometimes the best thing to do is to wait for the bandwagon to pass and see what is left behind.

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