ARMONK, NY – A quick look at the headlines lately shows that "big data" is a big deal. Healthcare is just starting to realize the potential of gathering, drilling down, mining and analyzing those massive troves of information – and more and more signs point to big data analytics making a big difference.
Researchers see the potential for advancements that could lead to major improvements in public health. Vendors see the potential for new income from a new market.
But as with any term that gets tossed about this much, the question has to be asked could big data just be another buzzword? IBM doesn't think so.
The computing giant made news on the big data front more than once recently, first with its April 25 acquisition of Pittsburgh-based Vivisimo, and the next day with an announcement from SUNY Buffalo about multiple sclerosis research.
Vivisimo develops federated discovery and navigation software meant to help organizations access and analyze big data. With some 2.5 quintillion bytes of data created every day, IBM says the deal will help accelerate its big data analytics initiatives, helping organizations such as healthcare providers, government agencies and telecommunications companies navigate and analyze structured and unstructured data.
"Navigating big data to uncover the right information is a key challenge for all industries," says Arvind Krishna, general manager, information management, IBM Software Group. "The winners in the era of big data will be those who unlock their information assets to drive innovation, make real-time decisions, and gain actionable insights to be more competitive."
So, is big data as transformative as so many say it is?
It's a fair question, says Shawn Dolley, vice president and general manager of global healthcare and life science at IBM Big Data. (He worked for Marlborough, Mass.-based Netezza before its acquisition by IBM in 2010.) "From a healthcare perspective, the typical question I always ask is, 'Is this just a rebranding of business intelligence, now that data sizes have grown?’"
Doing it right depends how it's deployed, he says. "We talk to a lot of health systems, and the ones that we think are utilizing it well have a few things they typically do."
Most crucially, "they are [making] strides toward trying to create a biologically oriented, centralized, linked repository," says Dolley. "Some have a very clinical, focused approach: 'Let's do some gene sequencing near the bedside and optimize our cancer drug cocktail.' That's sort of proactive, tactical, specific, high-ROI to a single patient."
Dolley offered some advice on making optimal use of big datasets.