Why big data spends may see a sharp decline in 2 yrs: Gartner


Investments in big data may sharply fall in the next two years after witnessing a constant uptrend, says a new Gartner survey. The survey says that the number of companies that are constantly investing in big data will contract, leading to overall decrease in investments.

Organisations, according to the report, don’t intend to spend on big data because they are moving away from vague notions of data and analytics to specific business problems that data can address.

Big data is a collection of complex data that is analysed to reveal behavioural patterns or trends related to humans.

A big hurdle with respect to big data is to successfully get big data projects on to the production stage. “While nearly three quarters of respondents said that their organisation has invested or is planning to invest in big data, many remain stuck at the pilot stage. Only 15 percent of businesses reported deploying their big data project to production, effectively unchanged from last year’s (14 percent),” the report says.

“One explanation for this is that big data projects appear to be receiving less spending priority than competing IT initiatives,” says Nick Heudecker, Research Director, Gartner.

Only 11 percent of the respondents of the Gartner survey that have already invested in big data reported that their big data investments were as important, or more important, than other IT initiatives, while 46 percent stated that they were less important.

“This [lack of interest in big data] could be due to the fact that many big data projects don’t have a tangible return on investment (ROI) that can be determined upfront,” added Heudecker. “Another reason could be that the big data initiative is part of a larger funded initiative. This will become more common as the term “big data” fades away, and dealing with larger datasets and multiple data types continues to be the norm.”

Jim Hare, Research Director, Gartner, said that when it comes to big data, many organisations haven’t moved beyond the crafting stage.

“Industrialization — and the performance and stability guarantees that come with it — have yet to penetrate big data thinking,” he said.