How can we use data if we can’t interpret it? This week we look at Crunch Network’s article regarding the lack of data scientists to fill this critical gap.
The term “data scientists” was rarely used 20 years ago, even 10 years ago most employers didn’t grasp the value of this specific skill set. A data scientist uses a combination of computer science, statistics, operations research, engineering, business insights and strategy to interpret data and find key insights. Now, the term is widely used and it is one of the most sought after positions.
Employers have learned the value of and are beginning to seek out data scientists to better gain an edge against competitors. However, with more employers demanding this position, a global shortage of qualified data scientists is upon us.
This lack of qualified data scientists is due to the current amount of data science programs offered in universities. In the U.S. alone, 29 universities offer data science programs and only 6 offer programs for undergraduates. There are three solutions that could provide relief to employers:
- Increase the number of universities offering data science degrees
- Offer data science programs for undergraduates
- Launch programs that train analysts to become data scientists
This gap in supply and demand will not be an easy task to close. However, with the collaboration of employers and universities, it will be possible to prepare students to become successful employees.
Read Crunch Network’s original article here.
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