Gartner’s Hype Cycle for Big Data

Louis Columbus at Forbes.com surveys key big data forecasts and market size estimates, including Gartner’s recent Hype Cycle for Big Data. The winning technologies in the immediate future? “Column-Store DBMS, Cloud Computing, In-Memory Database Management Systems will be the three most transformational technologies in the next five years.  Gartner goes on to predict that Complex Event Processing, Content Analytics, Context-Enriched Services, Hybrid Cloud Computing, Information Capabilities Framework and Telematics round out the technologies the research firm considers transformational.”

More on the report from Beth Schultz at AllAnalytics:

Gartner’s Hype Cycle is extremely crowded, with nearly 50 technologies represented on it. Many of them are clustered at what the firm calls the peak of inflated expectations, which it says indicates the high level of interest and experimentation in this area. As experimentation increases, many technologies will slide into the “trough of disillusionment,” as MapReduce, text analytics, and in-memory data grids have already done, the report says. This reflects the fact that, even though these technologies have been around for a while, their use as big-data technologies is a newer development.

Interestingly, Gartner says it doesn’t believe big-data will be a hyped term for too long. “Unlike other Hype Cycles, which are published year after year, we believe it is possible that within two to three years, the ability to address new sources and types, and increasing volumes of information will be ‘table stakes’ — part of the cost of entry of playing in the global economy,” the report says. “When the hype goes, so will the Hype Cycle.”

About GilPress

I'm Managing Partner at gPress, a marketing, publishing, research and education consultancy. Also a Senior Contributor forbes.com/sites/gilpress/. Previously, I held senior marketing and research management positions at NORC, DEC and EMC. Most recently, I was Senior Director, Thought Leadership Marketing at EMC, where I launched the Big Data conversation with the “How Much Information?” study (2000 with UC Berkeley) and the Digital Universe study (2007 with IDC). Twitter: @GilPress
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