12 Big Data Trends Changing the Face of Business

Big data is slowly but surely changing the way companies do business. “There are different use cases in every industry,” says Ron Bodkin, CEO and founder of big data consulting firm Think Big. “Big data is unlocking an ability to work with data that has been stressed for a long time. There’s been a lot of pent-up demand.”

Here are 12 trends shaping big data and the future of business.

Updated on October 8, 2013

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The new cornucopia of public and private data is providing a new opportunity to mash up multiple big data sets to gain new insights beyond what a single big data set allows. “The highest value of big data is coming from combining big data sets together,” says Ron Bodkin, CEO and founder of Think Big, a big data consulting firm. For instance, Land O’ Lakes’ WinField business, a provider of agricultural seed and crop protection, combines big data sets—including weather data, soil moisture data, soil type data, seed data and more—to help its growers achieve maximum yields.

Many early big data projects were skunkworks projects intended to prove the value of big data, but that’s changing. “We’ve seen a lot of viral spread of success,” says Ron Bodkin, CEO and founder of Think Big, a big data consulting firm. “But we think there’s a better way than relying on skunkworks innovation. It’s about taking a more proactive approach to identifying where big data can really have an impact. We do think it’s important to have a proven test case, but with executive sponsorship you can get results a lot faster.”

Test-bed projects have dominated the big data industry for the past several years, but these days there are a lot more actual production projects, says Ron Bodkin, CEO and founder of Think Big, a big data consulting firm. For now, he says, these projects are largely about achieving data scalability and cost containment, like building a data lake, but the innovators who got started early are beginning to turn their attention to leveraging their new analytics capabilities for business transformation. “They’re spending a lot less time chasing down data and a lot more time actually looking at data and answering questions,” Bodkin says.

Perhaps unsurprisingly, business functions that generate and maintain revenue get the most investment when it comes to big data initiatives, according to Tata Consultancy Services. In fact, 55 percent of spending went into four business functions: sales (15.2 percent), marketing (15 percent), customer service (13.3 percent) and R&D/new product development (11.3 percent). Nonrevenue-generating functions get less investment: IT (11.1 percent), finance (7.7 percent) and HR (5 percent).