It was bound to happen sooner or later — degrees that didn’t exist 20 years ago because of the advancement, and wonders of, modern-day technology.
No, we’re not quite at the point of a Masters in Self-Driving Car Engineering (more to come here when Google perfects their machines in that department). But the need for data-driven decisions in organizations has given way to a ton of degrees capitalizing on this analytical bar being raised.
In fact, according to Paul Barth, co-founder and CEO of Podium Data, in a recent BostInno article, “in recent years, the number of Master’s programs in data science has grown from a mere handful to more than 170.”
And just running a simple search shows the explosion of these programs, from quite the esteemed list of colleges and universities:
- NYU: Master of Science in Data Science
- Columbia University: Master of Science in Data Science
- Bentley University: Masters in Marketing Analytics
- Stanford University: M.S. in Statistics – Data Science
- Michigan State University: MS in Business Analytics
These are some well-respected institutions of higher learning, no doubt. The question is, is the esteem still worth the investment?
There’s opportunity for both the less technical employee, and the one with the advanced degree, according to Aberdeen Group VP & Principal Analyst, Analytics & Business Intelligence, Michael Lock. Whether or not you should make a big — and costly — investment in a Masters in Data Science is something that’s completely dependent on the organization in which you plan to work.
“With more sophisticated data capture and processing capabilities today, the opportunities could be even greater for the more data-savvy users,” said Lock, with a nod to those who hold an advanced degree in analytics.
“Our research shows that more companies today are formalizing the role of data scientist, one specifically dedicated to generating game-changing insights from the growing mass of data in the organization. Other research suggests higher overall salaries and a lucrative career path for those in the data scientist / data analyst role, as well,” he continued.
Lock adds though that it’s completely unclear if this is a long-term or sustainable trend, and that this type of analytical culture could be completely the opposite case in an another organization.
In fact, many companies are building capabilities that would enable a non-technical user to navigate far more easier in a layer of quality, well-governed data. In other words, some are going the far-less-inclusive route of an “analytics for all” approach.
“Others may go the other route and look to up the analytical game of their less technically-inclined employees and build that analytical culture across the entire company,” said Lock. “The everyday user has broader access to data and a greater ability to transform it into useful insight.”
To sum up Lock’s advice: Do your diligence before you invest in a “Big Data” degree. If you’re at an organization long-term where a sales leader without an advanced degree is easily empowered to create mission-critical insights, it could be a big investment for no return.