Data scientists who visualize massive amounts of information and make it accessible to everyone are actually 'animators,' says one analytics expert.
Big Data Analytics Masters Degrees: 20 Top Programs
(click image for larger view and for slideshow)
If you've been reading InformationWeek's Big Data section for a while, you're certainly familiar with the term "data scientist," which generally refers to an individual skilled in multiple technical disciplines, including computer science, analytics, math, modeling, and statistics. This professional is adept at gleaning meaningful insights from massive data sets, and then communicating these insights to the rest of us, including tech-challenged and front-office types.
But when you think about it, what these information gurus really do is "animate data by bringing it to life," according to Guy Cuthbert, managing director of Atheon Analytics, a UK-based data analytics company located 45 miles north of London.
Formed 6 years ago, Atheon Analytics is a 10-person shop that analyzes very large sets of retail data for U.K. supermarket chains such as Tesco, Waitrose, and Sainsbury’s, as well as for a number of food suppliers, including Coca-Cola, Nestle, Weight Watchers, and Yoplait. "We specialize in visual analytics. Our big thing is taking relatively large data sets and turning them into rich, interactive applications," Cuthbert told InformationWeek in a phone interview.
As Cuthbert sees it, a data scientist is, in essence, an animator who sketches visuals to tell a story. "We tend to use the term 'data animator' because a lot of what we do is bring data to life and make it very humanly accessible," said Cuthbert, who called his job an "interesting hybrid," requiring both strong mathematical skills and a knack for human interaction.
That rare combination is what makes finding qualified data animators, or scientists -- take your pick -- so hard to find. "We tend to try to get computer science grads, but that's not always the best fit," Cuthbert said. "They certainly need to be strongly mathematical, but they also have to be very personable and have an innately inquisitive mind that's interested in finding the patterns in data."
In other words, all data tells a tale if you know how to find it. "There's an awful lot of value in data, in telling a story from it," said Cuthbert. "A tremendous amount of the work we end up doing is teaching people how to think creatively about what they're doing with their data."
One of the tools that Atheon Analytics uses to manage its clients' growing data sets is Actian Vectorwise, an analytic database that promises high performance on commodity hardware -- an important consideration for cost-conscious startups like Atheon. "We couldn't afford to go and buy a high-end Teradata device or whatever," said Cuthbert. "We had to find something that was relatively off the shelf that we could put on the servers we have here, and that we could deploy on our cloud platform as well."
Over the past two years, Atheon Analytics has found that many of its clients' massive data sets are growing too large for traditional databases, which is why nine months ago it decided to give Vectorwise a try.
The company has switched from SQL Server to Vectorwise for four to five projects thus far, Cuthbert said. "Queries that were taking 15 or 20 minutes to run were shot down to 3 or 4 seconds." The faster performance delivers a very significant advantage. "It changes the way people engage with information when they can manipulate it pretty much as quickly as they think of questions."
Emerging database technology promises to automate more analysis. Here's where it could replace relational systems. Also in the new, all-digital The Rise Of Semantic Databases special issue of InformationWeek: There's a big demand for big data and analytics experts. (Free registration required.)
6 Tools to Protect Big DataMost IT teams have their conventional databases covered in terms of security and business continuity. But as we enter the era of big data, Hadoop, and NoSQL, protection schemes need to evolve. In fact, big data could drive the next big security strategy shift.
Big Data Brings Big Security ProblemsWhy should big data be more difficult to secure? In a word, variety. But the business wonít wait to use it to predict customer behavior, find correlations across disparate data sources, predict fraud or financial risk, and more.