Well, turns out, we were on the right track.
According to an article in Forbes magazine, businesses are going to need data scientists to make sense of the mounds of data piled up from every direction, if they want to beat out their competitors. In fact, the skills of the data analyst are essential to the 21st century enterprise.
Dan Woods (@danwoodscito), the author of the Forbes piece, turned to Steven Hillion, vice president of analytics at EMC Greenplum, to get some insight into the importance of the role of the data scientist.
Hillion says data scientists are “analytically-minded, statistically and mathematically sophisticated data engineers who can infer insights into business and other complex systems out of large quantities of data.”
And Hillion says data scientists are an uncommon breed—they’re equal parts engineers, statisticians and investigative journalists/forensic reporters—which is why they’re in high demand.
So, if you want to ride the wave of this highly sought-after profession you should start brushing up on your hard and soft skills, he says.
First be sure you understand the business—nothing new there. Ask the right questions, listen to the answers—really listen—then dig deeper to find out what’s really going on.
For example, he says if the business execs tell you they want to understand year-on-year sales, digging a little deeper will enable you to determine they’re asking because sales are plummeting in the Northwest. Then ask, “Why do you think that might be happening?” So not only do you have to understand the business, you also have to be a good interviewer to be a data scientist, he says.
In addition, you have to hone your skills to your particular industry. If you work for a retail company, for example, Hillion says you have to have an in-depth understanding of the way prices and promotions work.
You’ll also need to be skilled in mathematics, statistics, modeling and data mining. According to Hillion, the best data scientists come from physics, bioinformatics and other applied fields, “because modeling and experimentation with real data sets is important in these fields.”
For Hillion, the data scientist needs to have technology skills for processing big data, the statistical and analytical skills for modeling the world and making predictions, and the skills to understand his particular industry. Add to those skills, a dash or two of communication skills. Shake—or stir—vigorously and you’re ready to get to work.
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Spotfire Blogging Team