What to Look For in a Master's in Business Analytics Program
Business analytics is so new that not all schools agree [...]
The COVID-19 pandemic introduced a new term to the popular lexicon: “social distancing.” According to public health experts, social distancing—coupled with the wearing of surgical masks—represented the best pre-vaccine defense against the spread of this dangerous virus.
How effective is social distancing? To find the answer, data scientists studied cell phone geolocation data to determine where people were—and weren’t—following good social-distancing procedures. By tracking phone users’ movements and correlating them to reported coronavirus cases, data science arrived at a definitive conclusion. The data demonstrated that “as person-to-person interactions… increased, there was a corresponding increase in confirmed COVID-19 cases.”
This is just one of many, many examples demonstrating how data science can be used to understand our world and formulate better strategies. With digital devices gathering data on everything from your shopping habits to your physical activity to population-wide trends, data science is positioned to play a crucial role in business, government, health policy, and education. It’s hard to see how that trend could reverse any time soon.
If you have an aptitude for statistics, computers, mathematics, and problem-solving, data science could be the career for you. Most data scientists hold a graduate degree, so if you’re considering this opportunity, you should also think about earning your master’s.
Many universities offer this degree in both full-time and part-time programs. Which is right for you? In this article, we explore the nine best reasons to earn a part-time data science master’s degree by addressing the following:
A master’s in data science is a graduate-level degree with a data science designation, such as:
Because data science is a new field that combines a number of disciplines, it is possible to work in data science with a related degree, such as:
As the field of data science establishes itself, the distinctions among these different degrees will grow clearer. For now, all can funnel into data science careers.
Data science is an interdisciplinary field that combines coursework in mathematics, statistics, computer science, business administration, and healthcare. And that’s just the tip of the iceberg;
according to Dr. Ganapathi Pulipaka, Chief Data Scientist at Accenture, data science blends“software engineering, predictive analytics, machine learning, deep learning, HPC, supercomputing, mathematics, data mining, databases (SQL, NoSQL), Hadoop, streaming analytics platforms for live analysis (Apache Kafka, Apache Flink, Apache Spark, Apache Impala), IoT platforms, edge computing, fog computing, networks, statistics, web development, cloud computing, data engineering, and data visualization.”
By collecting, sorting, and analyzing Big Data sets, data scientists can draw valuable insights about the past and use them to project future outcomes. It’s not hard to figure out how that can be useful to decision-making in everything from marketing to public health policy to sports management. Wherever large amounts of data collect—which is pretty much everywhere these days—data science is potentially useful.
Job titles for data scientists with a master’s degree can include:
A 2018 report from Burtch Works indicated that 43 percent of all data scientists hold a master’s degree as their highest degree. OK, you say, that’s less than half; that means you have still have a pretty good chance of getting a job with just a bachelor’s degree.
We hate to burst your bubble, but sit down: the other shoe is about to drop. Another 48 percent of data scientists hold a PhD as their highest degree. Only one in ten data scientists currently scrapes by with only a baccalaureate. And the other data scientists probably make them clean up the conference room after meetings.
Not all of those graduate degrees are data science degrees per se. One-quarter are in mathematics or statistics. One in five is in computer science. 20 percent hold a degree in the natural sciences, and nearly as many—18 percent—have engineering degrees.
You don’t technically have to have a graduate degree to become a data scientist, but your chances are much, much better if you have one. That’s a trend that should only grow more pronounced as more graduate-level data scientists enter this increasingly complex field.
You don’t have to have one, but nearly half of all data scientists do (See Do I need a master’s to work in data science? above for details). Some companies—Google, for one—pride themselves on the number of PhD-level data scientists they employ.
University and Program Name | Learn More |
Tufts University:
Master of Science in Data Science
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Boston College:
Master of Science in Applied Economics
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Boston College:
Master of Science in Applied Analytics
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Merrimack College:
Master of Science in Data Science
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Stevens Institute of Technology:
Master of Science in Data Science
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Each data science master’s program offers a unique curriculum. All, however, focus to some extent on:
The online data science master’s program offered by the University of Virginia (Main Campus) includes the following courses:
New Jersey’s Stevens Institute of Technology offers an online data science master’s with a similar curriculum:
Some data science master’s programs offer students the opportunity to specialize in a more specific field. After completing required core courses, students develop their specializations, or concentrations, through elective courses. Specialization areas include:
Once you decide to pursue a master’s in data science, you still face a significant question: should you attend a full-time program or study part-time? Each has its compelling reasons. Below we explore nine reasons why part-time study makes sense to so many.
Full-time graduate school degree programs are as advertised: they require a full-time commitment. As a full-time student, you may find time for a bit of project work or a part-time job, but chances are you will be fully occupied with school work. Yes, you’ll complete the program sooner, but while you’re studying, that’s pretty much all you’ll do.
Part-time students can, and typically do, continue to work full-time. As a result, they don’t forfeit the one- to two-years of income that full-time students forgo. And—assuming they work at a data-science-related job—they will have the opportunity to apply their classroom learning to real-world applications as they learn it. Part-time study provides unique opportunities to practice and reinforce school skills, a process that promotes retention.
If your employer has any interest in keeping you around long-term, they want to see you working to improve your skills and knowledge. There’s no better way to do that than to pursue a graduate degree, particularly in a field with so many applications in the workplace. Not only will you show your boss that you’re ambitious, you’ll also get the chance to demonstrate your ability to manage your time, handle a heavy workload, and succeed at difficult challenges. All of those are huge plusses that can only help your career.
Most employers encourage their employees to improve their skills through professional development, trainings, certifications, and graduate programs. Some do more: they offer to kick in to help defray the cost of learning. Some even foot the entire bill. Check with your employer to learn whether they offer an education benefit. You could be sitting on a free pass to a data science master’s degree program.
There’s a lot to learn in a data science graduate program: lots of mathematics, lots of statistics, lots of computer science. You’ll need to memorize vast amounts of information and learn how to put it to practical use. Not everyone is comfortable learning at the firehose pace set in full-time programs. Part-time programs parcel out the learning in smaller chunks so you have more time to absorb it, practice it, and incorporate it into your repertoire of skills.
Taking a longer time to earn your degree doesn’t just reduce the intensity and pressure of the learning experience. It also gives you more time to absorb your learning and to see where it takes you. With the luxury of a few extra semesters, you’ll have time to develop an interest in, and aptitude for, artificial intelligence or data management or predictive modeling, and to tailor your study to pursue that interest. That’s less likely to happen during a shorter, concentrated full-time program.
Full-time programs typically meet on weekdays, during the day. Part-time programs don’t, because they are designed for working students. Classes are scheduled for students’ convenience: in the evenings and on weekends.
Online programs offer even more flexibility and convenience. If you enroll in an online program that holds synchronous (i.e., live) online classes, live sessions typically meet once or week, and in some cases even less often than that. And some online programs are entirely asynchronous, meaning students complete online courses entirely on their own schedule. Pre-recorded lectures, assignments, and other content are accessible 24/7, so students can work anytime anywhere they have access to the internet. Are you a night owl? An early bird? Want to grab a quick 15-minute study session during your lunch break? With online study, that’s doable.
Part-time study spreads school costs over a longer period, reducing the financial hit you take each time you pay your tuition. It may even keep per-semester costs low enough to obviate the need to take student loans. Reducing the financial burden of school should help reduce the stress of the graduate school experience.
Earning a part-time data science master’s degree means earning a data science master’s degree, and that means you’ll get all the same benefits full-time students derive from their degrees. You will develop expertises and skills you never before had, and the confidence to use them. And you’ll have an impressive degree to show your employer and other prospective employers
Full-time students don’t have a monopoly on access to faculty, peers, and alumni. Prestigious schools earn their reputations in large part for the networks into which they introduce students. You’ll belong to that network and derive the same benefits as full-time students.
Among the nation’s top Master of Science in Data Science programs are:
You’ll find excellent online Master of Science in Data Science programs at:
Relatively inexpensive Master of Data Science can be found at:
You’ll find affordable online Master of Data Science programs at:
Questions or feedback? Email editor@noodle.com
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