Big Data is a big buzzword within the IT community these days, with a growing percentage of businesses collecting and analyzing epic reams of information—but to what end?
In order to maximize return on investment, not only does a business require qualified analytics experts, but also needs to figure out how this information will grow revenue and better serve customers. Otherwise, a Big Data investment will only result in diminishing returns.
According to a recent report from research firm IDC, worldwide Big Data technology and services will grow from a $3.2 billion market in 2010 to $16.9 billion in 2015, representing a compound annual growth rate (CAGR) of 40 percent. In addition, the report noted a shortage of trained analytics and Big Data technology experts. (Although this labor-supply constraint may inhibit the adoption and use of Big Data technologies, it might have the side effect of encouraging vendors to deliver Big Data technologies as cloud-based solutions, which don’t require the infrastructure and employee investment of on-premises solutions.)
Indeed, ferreting out a qualified Big Data analytics expert is no small task. “Finding a big data specialist is a blend of traditional and very specific new skills—for starters, this is PhD territory. A Computer Science degree—preferably a PhD—is a must, and look for expertise in machine learning, statistics, and natural language processing,” said Alice Hill, managing director of online IT recruiter Dice. “But academics need not apply—big data takes that foundation and marries those skills to newer technologies like Hadoop and NoSQL.”
While Hill admits Dice doesn’t yet have good salary information for Data Scientists (there are only 19 positions for data scientists on Dice, evenly split between consulting and working directly for a company), she does know that tech professionals with PhDs are seeing stronger increases in average salaries. For 2011-2012, that average is $112,755, up 13 percent year-over-year. Compare that to a two-percent salary increase across all tech jobs, according to the most recent Dice Salary Survey.
Plan of Action
Even more important than finding a qualified Big Data analyst is a plan of action for the data itself. IDC’s program vice president of business analytics Dan Vesset said many companies jump into the technology without linking it to their business goals and strategies. “They don’t follow through the full process from data collection to a final action with the customer,” he said. “It takes a little bit more effort—the business side has to be closely involved, or hopefully even lead, that process. The key is to ensure that there is a tight communication line with IT.”
Having a strategy and vision for collecting and storing information is a critical part of maximizing investment in Big Data technology. “You could be collecting a data set for your customers for sales, for customer service, for inventory or for compliance issues,” Vesset added. “Look for the broader implications of data collection.”
INTTRA, a provider of e-commerce solutions to the ocean freight industry, uses EMC’s Greenplum Data Computing Appliance (DCA) to extract answers from large volumes of data its customers find in almost every port around the globe. Anthony Costa, vice president of technology and customer experience, suggests the company’s Big Data strategy allows it to become a data predictor.
“Where many companies are just looking at Big Data as a mechanism to grow their own business, for us, we’re looking at our data as a source of new products and new information out in the market,” he said. “Our strategy around how we exploit the data we own is both for internal and external consumption, and the bounds are endless. We’re at the tip of the iceberg.”