data analytics

Is this the new class every student should take?

Data analytics, 101: The class your students need to take today for tomorrow.

With the high-school graduation season over, it’s time for grads and parents alike to celebrate and relax a bit – and maybe enjoy a long summer before recently minted graduates start college or a new job.

But here is something to contemplate (hopefully not too strenuously) over the coming summer weeks and months: What is the next learning step in the graduate’s preparation for a future career?

Whether a recent graduate plans to study 18th Century English literature in college or jump right into the workforce in any number of jobs, I have a one-word suggestion for them: Data.

Specifically, start learning about the analysis of data.

As seemingly odd as that might sound – perhaps even odder than the elder gentleman who recommends “plastics” to the young Dustin Hoffman character in the classic movie “The Graduate” – the simple fact is that our lives and careers, moving forward, will be increasingly influenced and determined by data analytics in just about every field, from what consumer products we buy to the type of medical treatments our doctors prescribe.

The data analytics era is already here. We see it every time we surf the web and those same pesky advertisements keep following us around, from site to site, no matter how much we try to lose them. Those ads are the result of data-analytic computations by Google and others designed to specifically figure out, mathematically, our consumer interests based on past purchases and web browsing histories.

As ubiquitous as this type of data analytics may already seem, we haven’t seen nothing yet, as they say, and it’s going to change the way we live and work. This data revolution is, ultimately and obviously, the result of the huge leap in recent decades in computer technology and the reams of data generated and collected by corporations, academic and public policy researchers and others.

But it’s only been recently that many have started to ask: What do we do with all this data, and how do we do it? In a nutshell, data analytics is about humans telling computers, via computer coding, what they want so that computers can tell humans what they want – and what they may well need.

And this means that humans – especially those young ones just starting out in their careers – need to learn how computers “think,” or, more accurately, how they’re coded to make computations that impact our lives.

(Next page: The need for Data Analytics 101)

The Need for Data Analytics 101

This need for “computational thinking,” as some are now calling it, is one of the reasons why President Obama, just prior to leaving office, launched the “Computer Science for All” initiative, designed to introduce more people to the art and science of coding. It’s also one of the reasons why, as the New York Times noted in a recent article, that computer science is now the most popular major at many of the Ivy League schools, as well as at prestigious non-Ivy schools such as Stanford, MIT and Tufts.

Those not majoring in computer science, including many classic liberal arts majors, are also showing an interest in these types of courses. These students realize that, at some level, computers, coding and data-analytics are going to shape their lives – and they better start learning, at the very least, the rudiments of computers and computer coding.

But data analytics, a relatively new field of study, goes much further than learning the basics of computer coding. It’s ultimately about what questions need to be asked about data; how to ask those questions; and then how to specifically tell, or code, computers to sift through data to arrive at potential answers.

Think about the future of medicine. Today medicine is not personalized. But with the availability of electronic medical records and genomic information, we are approaching a world where medical treatments informed by analytics will be targeted for specific patients.

Now think of other fields that can benefit from intense data analytics – airline travel, retail operations, entertainment, manufacturing supply chains or, if you’re a literary professor after getting your doctorate in 18th Century English literature, analyzing the number of times authors reference certain words or phrases to better gauge what they’re thinking and conveying.

This burgeoning interest in data analytics is spreading – and spreading fast.

Last year, I led the development of a new master of business analytics program at the MIT Sloan School of Management. We started with 300 applicants for a class of 16 students. This year: We had 900 applicants for a class of 30 students. My online MOOC (“Massive Open Online Courses”) class at MIT – entitled “The Analytics Edge’’ – now attracts tens of thousands of people from around the world.

Other universities are experiencing the same surge in interest in business analytics – and I firmly believe the trend will rapidly expand to community colleges and other centers of learning, including, perhaps, even some high schools. Why? Because data analytics is the future (like it or not) and we all need to know how it works in order to better understand how it’s shaping our lives.

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