University Web Developer Programs Must Prep Students For Big Data Era

Big data is playing a monumental role in economic development in 2019. It is being used in every industry from healthcare delivery to insurance modeling to political science. According to economic analysts, the market size for big data is currently estimated to be $203 billion.

Unfortunately, there is a growing shortage of data scientists. As we pointed out in a previous post, a white paper from PwC shows that the time that it takes to fill a Data scientist job is twice as high as the national average.

Universities across the country are going to need to educate students about the future of big data. Even students that are not studying the field of data science must understand the role that it will play in shaping their future profession. They can’t escape its relevance in the new digital era. University department heads are going to need to discuss the relevance of big data in the future workplace and propose ways to include it in their coursework.

Joshua Eckroth of Stetson University wrote a white paper on the different factors that universities need to evaluate while educating their students about big data.

Here is an excerpt from his paper:

“Stetson University, a small private liberal arts college, recently introduced an interdisciplinary Data Analytics minor that is designed in part to “prepare students for entry-level jobs in fields that apply Data Analytics and for graduate work in disciplines that utilize Data Analytics.” In addition to a variety of core courses that cover programming, statistics, and databases, students may choose one of several data analysis courses.”

His goal was to get a better understanding of the problems that colleges face with teaching big data, as well as to highlight the factors they should be emphasizing as they head into the 21^st Century. Some of the most important topics that Eckroth covered include the following:

• Necessary techniques and tools for different types of big data applications
• Skills needed to use these tools to address different challenges
• Teaching students to evaluate trends in data technology

In order to address these topics, educational institutions are going to need to overcome the barriers to covering big data courses in greater depth. They need to be cognizant of the obstacles that are preventing them from doing this.

Why have universities overlooked the importance of big data?

Any technology evangelist worth his salt will point out that big data is transforming every major sector of the economy. Nevertheless, educators have a major blind spot for big data. Here are some of the reasons.

Many technology educators are completely out of touch with current developments in the workplace

Many college instructors are vastly out of touch with the developments that are taking place in the workplace. While I was living in Northern California, several of my colleagues provided guidance to college professors teaching web development courses at a local community college. Many of these instructors were still teaching their students to use Flash to make websites 15 years after that technology was obsolete. They clearly don’t pay a lot of attention to these changes, so they aren’t even aware of the importance of react development.

It clearly is not surprising that many professors are unaware of the trends in big data. They don’t recognize the significance, so they don’t pass that information along to their students.

Some professors don’t feel it is applicable to their own discipline

Many people mistakenly believe that big data is only relevant in certain fields, such as financial services and healthcare management. This is obviously not the case. Big data is incredibly important in many fields. Professors in those fields need to understand its applicability and cover it in their own coursework.

There is a lack of data scientists in academia

Addressing the pipeline problem of data scientists is going to be essential as we move into the future. This is only possible if there are more professors teaching it. Since many data scientists are not going into academia, this is going to curtail the supply of future data scientist. This is something that needs to be addressed. Universities should look to increase funding for professors teaching best essential yet elusive discipline.