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Big Data: What Makes a Data Scientist Good?
The rise of Big Data brings along with it a need to have skilled workers that can analyze and make sense out of all of it. These workers are being called ‘data scientists.’
Mike Driscoll, the founder of Big Data company, Metamarkets, said that a data scientist can be thought of as “the interdisciplinary athlete of the modern organization.”
Who are data scientists today? A survey by SiSense found that data scientists are mostly male — 80 percent. 85 percent of them have college degrees; 39 percent have a Master’s degree; and 5 percent are PhD’s.
So we know a little bit about the demographics of a data scientist, but what does it take to be a great data scientist? Bill Franks, chief analytics officer for the data warehouse appliance vendor Teradata, told SearchBusinessAnalytics.com that “As much as you’d like to follow the book and go by what the formulas say, the data is never as complete as you’d like, the data is never as clean as you’d like, and the problem is never as well-defined as it would be in a textbook. The really good analytics professionals and data scientists are those that are able to understand the business problem; they’re able to apply creativity and present the results well.”
Tom Wheeler, senior vice president of development at customer interaction analysis firm ClickFox, said in a Forbes article that “A data scientist can find patterns in data that you haven’t sent them to find. You don’t send a data scientist for a specific business function; you provide a massive amount of data and free rein to use their skills to discern patterns in that data… Companies are designing very specific schemas, going after specific business problems, and trying to reduce everything to transactions and customer-based data. But they’re not getting much value out of the investment in all of that storage capacity. What a data scientist gives you is the ability to look at the data in a different way than throwing classic BI tools at it or trusting an outsourced solution to do the statistical analysis for you.””
Jason Ward, country manager for Ireland, EMC, said that “Chief executives should get ahead of the curve now and start identifying people in their organizations who have proven themselves as both technically adroit and analytically creative. It is important not to confine the review to IT professionals. The big data team should draw heavily from disciplines capable of thinking beyond typical linear problem-solving. Then, invest in them through training and certifications in big data analytics and data science, which colleges are beginning to develop”
