Credit: Big data storage image via Shutterstock
Big data, as the term suggests, is putting scads of new digits on IT's plate. It also means big storage needs. Sensing that there's money on the table, the financiers have opened their purses to let their IT departments acquire the equipment or solutions that meet enterprise needs.
Storage, in fact, will account for the largest chunk of all spending in the build-out of big data technology and analytics systems (BD&A), according to two in-depth studies just released by research organization International Data Corp. (IDC). Storage will have increased at a compound annual growth rate of 53 percent between 2011 and 2016, IDC found.
The amount of data generated, processed and stored by most organizations will continue to grow aggressively for the foreseeable future.
"Storage will be one of the biggest areas of infrastructure spending for big data and analytics environments over the forecast period," said Ashish Nadkarni, IDC's research director, storage systems. "Revenue from storage consumed by BD&A environments will increase from a mere $379.9 million in 2011 to nearly $6 billion in 2016. This growth will come largely from capacity-optimized systems, including dense enclosures; however, software-based distributed storage systems with internal disks to store post-processed data will also be embraced by some users."
Additionally, businesses will continue to tap into newer data sources as they move their analytics efforts from search to discovery. This shift will accelerate spending on infrastructure and data organization platforms.
Businesses will continue to struggle with what data to analyze, how to store it before and after it is analyzed, and how to feed the results of data analysis back into the business, IDC said.
When it comes to having the greatest influence over data-analytics infrastructure, IT trumps operations by a significant margin, IDC said. Regardless, the research found, there is universal agreement that improving customer satisfaction is the greatest challenge to be solved with data-analytics deployments.
And all that data takes a lot of storage.
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