eLearning Is The Key To Solving The Big Data Skills Gap

eLearning Is The Key To Solving The Big Data Skills Gap
Summary: Big data is changing the way companies of all kinds do business. The eLearning industry needs to rise to the challenge of preparing a whole generation of big data professionals to meet the growing worldwide demand. Here's what they'll need to do.

Is eLearning The Key To Solving The Big Data Skills Gap?

Over the last few years, the rise of big data has created an entirely new industry right before our eyes. Today, companies all over the world are integrating analytics and machine learning platforms at every level of their operations.

The Skills Of The Future

Big Data has even become a critical part of the future of eLearning, as well. The new technology will help to shape the next evolution of eLearning platforms and tools by helping educators to tailor courses and student interactions to suit the specific needs of their clients. Before that can happen, though, the eLearning industry is going to have to help stave off a Big Data crisis in the making.

The boom in Big Data has thrown down a gauntlet, of sorts, for everyone in the eLearning industry. The reason is that there's a looming labor shortage in data science-related fields, and there is every reason to believe that the eLearning industry is going to be the key to solving it. It's going to take a renewed focus on building comprehensive preparatory eLearning coursework from the K-12 level all the way up to graduate programs, and there's no time to waste.

Teaching From The Ground Up

For the eLearning industry to build a pipeline of talent to meet the exploding demand for data science skills, it's important to get as early of a start as possible. In practice, this means the development of eLearning solutions that introduce data science topics to K-12 learners. In the traditional learning arena, a company called Bootstrap is already providing courses to schools all over the United States that do just that.

On the eLearning side, there's a platform called Code.org that provides data science courses to students and teachers in the K-12 space. They offer courses aimed at learners in grades K-5 and have separate courses that cover grades 6-12. Code.org claims that a full 25% of U.S. students have accounts on the platform, which should help to create a solid talent base for data science programs at the university level. They're not alone in the K-12 space, though. New York-based firm Tuva is also making inroads into the data science eLearning market with a suite of tools and courses that may be accessed by teachers and schools, or by students directly.

Advanced Degree Programs

In addition to addressing the need for data science education in early education, it's also necessary for the eLearning industry to scale up degree programs in data science-related fields. At present, at least in the U.S., a masters-level education is the norm for professionals in data science careers. In this area, eLearning companies in the U.S. are finally beginning to catch up to the kinds of offerings that have been common overseas for several years.

For example, RMIT University, based in Melbourne, Australia, has a robust online postgraduate program that allows qualified students to earn degrees in several data science-related fields. The RMIT approach is quite comprehensive, and students can even earn a master of engineering management degree, with a focus on technology. While that degree isn't limited to data science, it does reflect an acknowledgment that the complex IT systems and engineering teams that support them are, in turn, going to spur new demand for managers in organizations worldwide. That's the kind of approach that U.S. eLearning platforms will need to adopt if they'd like to keep pace.

The eLearning Advantage

Through efforts such as those outlined above, the eLearning industry should be able to respond to the data science skills demand in short order. Since eLearning platforms tend to be more agile and adaptable than their institutional counterparts, the industry is uniquely suited and well positioned for just such a challenge. In the long run, this is also a lucrative effort for the industry as a whole, and it is one that will bear fruit for years.

There's also a bit of self-interest at play, as well. After all, data science is going to shape the eLearning industry well into the future, so the very process of meeting the demand for these skills will assure continued success for the industry for a long time to come. It's a rare win-win scenario for companies in the eLearning market, and embracing the challenge represents an investment that is sure to pay off both directly and indirectly for all involved.