95 percent of business struggle with unstructured data, according to Kommando Tech. That creates opportunities—plenty of them—for data analysts with the right skillset. A master's in data analytics can provide that skillset and boost your income in the process—analysts with a master's earn, on average, $15,000 more than professionals with just a bachelor's.
One in four hiring teams looks for candidates with a graduate education, according to Northeastern University. If you're looking for one of the top analytics jobs—typically listed in the data scientist category—know that over 40 percent of data scientists have at least a master's degree. Nearly half have the more-advanced PhD degree. Fewer than 10 percent have a bachelor's degree only.
Still, deciding to earn a master's can be a little like jumping headfirst into a lake without knowing how deep it is or how many venomous snakes there are. You should consider the potential opportunity cost of missing two years of work—which is how long it takes to complete a master's full-time—and how much debt you will accrue as a result.
With degrees from top universities potentially costing more than $100,000, you can easily end up committing a good chunk of your post-graduation salary towards student debt. The good news? Those wanting to pursue a career in data analysis might not need to attend a prestigious university to land a high-paying data scientist position. Numerous reputable schools offer a master's in data analytics for a fair price, allowing you to get the right skills without the risk of being thrown into an 18th-century style debtor's prison.
Learn how even the most affordable data analytics master's degrees can lead to a slew of job offers. This article will cover:
A Master of Science in Data Analytics caters primarily to experienced analytics professionals. Many schools look for applicants with extensive work experience—sometimes between five and ten years—as data engineers, architects, or analysts. Even data scientists sometimes apply to a data analytics program.
Typing "what is a master's in data analytics" into your Google search bar will likely net you pages of results for business analytics and data science degrees. These are slightly different from data analytics; knowing the difference is important and can help define what you'll learn in a data analytics master's program.
It's easy to conflate master's in data science and analytics degrees; depending on the programs you compare, the two can be nearly identical. Both prepare graduates for computer science careers by covering cloud computing, data mining, and big data analytics. The main difference is that data science programs typically take a deeper dive into subjects like:
Graduates with a master's in data science generally have a higher earning potential than those with a data analytics background, but it depends on how they use their degree. Master's in analytics graduates can become high-earning data scientists with the right work experience, meaning they can potentially earn data science money.
A business analytics program also teaches data techniques and statistical methods but focuses on measuring and improving outcomes and decision-making in business. Again, many of the same courses are covered, but the focus differs. Business analytics graduates can become business analysts and marketing analytics managers, as well as data scientists. Confusingly, data analytics and business analytics programs are usually both offered through a university's school of business.
This depends on the program that you attend and its focus. Most include coursework on:
From there, degree programs branch out, allowing students to specialize in a single area of analytics. Duke University asks students to choose from numerous focuses, including machine learning and biomedical engineering. These concentrations likely include courses titles that trend towards data science, including:
Keep in mind, some schools may allow you to concentrate in analytics as part of a data science program. Indiana University - Bloomington offers four "domain areas" data science students can choose from:
Additionally, students need to complete core courses, electives, and a capstone project to graduate.
You can earn an affordable master's in data analytics in both traditional and online learning settings. Here, affordable is defined as anything under $1,000 per credit—when it's possible to calculate on that basis. Several programs on this list charge under $500 per credit.
Many public universities offer in-state students a discount and charge out-of-state students more. Our list includes the in-state rate, which typically applies to the greater number of students.
Keep in mind that tuition is not the only expense you'll have in graduate school—books, room and board, and even health insurance are all potential fees you'll need to cover. Additionally, some programs may charge a different rate for part-time students than full-time ones. The numbers on this list should be taken only as a starting point for calculating how much you'll pay.
Some of the most affordable master's in data analytics can be found at:
The short answer question is no; the long answer is more complicated. Tuition is generally the same for online master's degrees as for traditional programs—at least for schools that offer both options. Georgia Tech is somewhat of an anomaly because tuition for its in-person master's in analytics is far more expensive than the online Master of Science in Analytics.
The real benefit of attending an online master's program is its flexibility. You may be able to work while in school, which most graduate students don't have the time to do. In a sense, it's "cheaper" because you may be able to avoid taking out loans. You'll also avoid relocation and/or commuting costs, which can be significant.
Keep in mind, many schools also offer hybrid programs, which involves splitting time between online courses and a traditional classroom. These offer the flexibility of an online program with on-campus networking opportunities.
So, is affordability better? It depends on your goals. Duke boasts of graduates that land jobs at top companies like Google and Apple. Graduates of the 2018 data analytics class at Georgia Institute of Technology's earned close to $100,000. The benefits of attending a top program include networking opportunities and facetime with professors who are experts in their field, which can precipitate a better career trajectory.
On the other hand, UT San Antonio graduates earned a median of $109,000—higher than Georgia Tech graduates. Some data even shows that your salary is actually more tied to the prestige of your bachelor's degree than your graduate program.
The decision to attend top school often comes down to career goals. According to a Fordham University graduate school blog post, university rankings matter most for those who want to pursue academia—meaning PhD students. There are many accredited (critical) and well-respected schools that aren't Ivy League institutions.
In recent years, comparable alternatives to graduate education have emerged. Certificate courses in analytics offered through well-regarded schools like The University of Texas at Austin and Boston University can be a great way to save time and money while rounding out your education.
The UT Austin Data Analytics Certificate Program covers many of the same topics as a master's degree, though in less time and for less money. It takes full-time students 20 weeks to complete the program (40 for part-timers) and costs $5,900 ($6,900 for part-timers). Topics include:
While UT Austin requires applicants to have at least two years of professional work experience, Boston University does not—though they may be required to take an introductory statistics course. BU charges part-time students $490 per credit, though that number can increase drastically for full-timers.
Boot camps are also increasingly viable ways to supplement your education in analytics. Again, they cover many of the same skills that you'll need for an analytics career and are frequently geared towards increasing employment potential. Boot camps can be found at universities, such as Georgetown University, or professional organizations like Springboard. These courses typically last a few months and cost a few thousand dollars—Springboard's is $5,500 while Georgetown's is $6,995.
To get an affordable graduate-level education in analytics, you cannot be afraid to think outside the traditional data set.
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