The hype may be cooling but Gartner finds that big data implementations are actually heating up

Almost three quarters of organizations surveyed by technology research outfit Gartner have invested or plan to invest in big data in the next two years.  The analysts also found a six per cent drop in the number of organisations still gathering knowledge about big data.

The bottom line from the study is this; organisations are now moving to the next steps of experimentation and investment. Gartner also reveals a seven per cent increase in organisations exploring opportunities by utilizing pilots and experiments.

“Last year, we said 2013 was big data’s year of experimentation and early deployment,” said Gartner research director Nick Heudecker.

“Big data investment continues to be led by North America, with 47 percent of organizations reporting investment, up from 37.8 percent in 2013,” he said.

“Big data can help address a wide range of business problems across many industries and for the third year in our study, both enhancing the customer experience and improving process efficiency are the top areas to address,” according to Lisa Kart, research director at Gartner.

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(Research Director, Gartner,  Lisa Kart)

Gartner noticed strong investments in customer experience, particularly in transportation, healthcare, insurance, media and communications, retail, and banking.

According to the study, “The other year-to-year changes in the survey findings are a function of the adoption stage. As organizations move beyond knowledge gathering and developing a strategy to making investments, piloting and deploying, the challenges they face become more practical”.

  • Organisations with no big data plans must determine how to get the value out of big data and they must define a strategy
  • Organisations with plans must acquire the skills and capabilities as well as they have to get the funding.
  • Organisations that are further on the investment scheme must assess risk and governance issues

So far, organisations have mainly focused on data volume rather than on data variety. Both require significant investments though. Data volume requires investments in compute capacities and increased storage. As for data variety, it requires not only increased storage capacity, but also a different set of tools and skills.

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