Data Science

Why Get a Master of Science in Data Analytics and Visualization?

Why Get a Master of Science in Data Analytics and Visualization?
Students in a master's program in data analytics and visualization develop precise skills and knowledge that make them valuable assets to a range of industries. Image from Unsplash
Elen Turner profile
Elen Turner January 6, 2020

A picture is worth a thousand words, but what is its value in gigabytes? With a Master of Science in Data Analytics and Visualization, you'll interpret big data sets and convey them graphically in ways that illuminate their meaning.

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If you have a knack for numbers and enjoy piecing together data to come up with big-picture solutions, a Master of Science (MS) in Data Analytics and Visualization (DAV) may be the right graduate degree for you. Careers in this field involve data management, modeling, interpretation, and reporting for private businesses, public and nonprofit institutions, and government entities.

In this article we'll cover:

  • Possible fields and career paths for Master of Science in Data Analytics and Visualization
  • Prerequisites for a Master of Science in Data Analytics and Visualization
  • Top schools for a Master of Science in Data Analytics and Visualization
  • Commitment required for a Master of Science in Data Analytics and Visualization

Possible fields and career paths for a Master of Science in Data Analytics and Visualization

A master's program in data analytics and visualization teaches you how data operate within society, media, and governmental structures, as well as how to gather, store, and present data. It explores the possibilities, implications, and limitations of data, and how to communicate raw data in digestible ways for business, government, or lay readers who can't interpret that data themselves.

Students in a master's program in data analytics and visualization develop precise skills and knowledge that make them valuable assets to a range of industries. Employers of data analysts include:

Almost all job titles associated with an MS in data analytics and visualization include the word "analyst" in them. You'll be required to think creatively and analyze problems and solutions. These jobs include:

Salary.com reports that data visualization specialists earn an average annual base income between $71,913 and $97,616. Payscale sets the average salary for data visualization specialists at $77,425, with another possible $14,000 in bonuses, commissions, and profit-sharing. Average annual income for data analysts is lower: Glassdoor estimates data analyst income at $59,782, plus another $1,000 to $12,500 in incentive payments.

As in most fields, improving your earning potential means building experience and extra skills. Some data analysts eventually return to school to train to become data scientists. This profession, which requires programming skills, can pay substantially more than data analytics and visualization.

As technology and the means through which we generate data develop, so too should the opportunities for those holding an MS in data analytics and visualization. It's safe to say that the field will look different in the next decade than it does today, but the prospects for master's program graduates should remain hopeful.

Prerequisites for a Master of Science in Data Analytics and Visualization

Generally, MS in data analytics and visualization programs require applicants to hold a bachelor's degree in information science, computer science, or statistics. Some admit students with degrees in mathematics. Many programs—the MS in data analytics at Georgia State University, for one—offer remedial classes for students to develop the skills required to begin the master's degree. These classes typically do not count toward the master's and must be completed before master's work can commence.

You'll also be required to have strong technical skills and knowledge. Experience with machine learning systems is also a plus. While many MS programs teach about the mathematical, statistical, and computing programs necessary to study and work in the data analytics field, some institutions prefer applicants who already have a working knowledge of the relevant programs and tools. Aptitude in the following should bolster your application:

  • Structured Query Language (SQL)
  • SPSS software for statistical analysis
  • SAS data analysis software
  • PowerBI business analytics service
  • R, Python, Scala, and Java programming languages
  • Spark open-source computing framework
  • Predictive modeling algorithms

Any certifications you have earned will likely impress admissions officers at Master of Science in Data Analytics and Visualization programs.

If you're especially interested in the data visualization side of this degree, it helps to have some kind of artistic, creative, or graphic design skills. It isn't essential, however, as many data analysts work with graphic designers to produce visuals.

While you're completing your bachelor's degree, consider pursuing an internship in statistical analysis, or entry-level work experience as a statistical assistant or technician. These will provide hands-on experience that you can put to use in your master's degree, as well as help you decide whether this is the career path for you. An internship or job experience could even speed up the MS down the track, as when courses have a flexible duration depending on your prior knowledge and skills.

Top schools for a Master of Science in Data Analytics and Visualization

Some schools offer master's degrees called Master of Science in Data Analytics and Visualization, while others offer similar programs under a different designation, such as:

If you're interested in studying both the data analytics and the visualization side of this degree, make sure to carefully check what is covered in your degree coursework before applying. Some schools focus more heavily on one aspect than the other, and not all programs with similar-sounding names focus on both.

Data visualization seeks to present collected data in a comprehensible graphic medium so that people not trained in this field can easily understand it. Mathematics and science students who also have an interest in the arts and communication, and those who may possess some artistic or graphic design talent, may find this a fruitful line of study to pursue. New York City's Parsons School of Design, at The New School, is one of the few institutions in the country to offer an MS in data visualization.

Many universities partner with corporations and other organizations to provide their students with internships or to work with students on capstone/research projects. These partnerships can provide invaluable real-world training. As you shop for programs, research the school's partners; they will likely be listed on the program website. If not, ask an admissions officer.

What are the most respected data analysis and visualization programs?

Many of the best places in the U.S. to study data analytics and visualization are in New York City. If you're not interested in living in a hectic, expensive city, fear not; there are some other options. We've listed some below:

Commitment required for a Master of Science in Data Analytics and Visualization

MS in Data Analytics and Visualization degrees typically require a time commitment of one to two years of full-time study. Many institutions offer online courses, if you're unable to attend classes in person. Most online students study part-time, taking closer to two-to-three years to complete the degree.

What is the average cost of completing a Master of Science in Data Analysis and Visualization?

Choosing a graduate program is not unlike choosing a car. If you shop around, you can find a functional degree at a reasonable cost. Think Honda Fit: it will get you where you need to go, but not everyone will be impressed by your wheels. At the other end of the scale are degrees that will impress everyone, but for which you may never get a return on your considerable investment. Think BMW 750. Yes, it cost way too much, but will you just look at it? It's amazing.

If you're looking for a bargain, start with state universities. Among private schools, Catholic universities are often less expensive than nondenominational schools. There are no absolutes when it comes to graduate programs, however. Some state schools charge hefty tuitions for their graduate degrees, and some private schools are surprisingly affordable. You simply need to do your research to figure out what program best fits your budget and career goals.

Less-expensive programs include the Master of Applied Statistics and Analytics at Central Michigan University, which costs $637 per credit hour for residents, $850 for non-residents (the program requires 30 to 33 credit hours, meaning it can be completed for as little as $19,110). At the upper end, a Master of Science in Analytics at Northwestern University costs $18,744 per quarter, or $93,720 for the five-quarter program. Most programs sit somewhere well between these two extremes, such as University of Washington - Seattle Campus, which charges $1,056 per credit for its 45-credit program (total cost: $47,520).

Financial aid and scholarships may be available to you, depending on your personal circumstances, your academic track record, and the institution in which you're looking to enroll.

Is data analytics and visualization right for you?

An MS in data analytics and visualization is a specialized degree. Graduates with a bachelor's degree in computing, mathematics, or statistics who are interested in data analytics can opt for a broader master's degree if they're not certain that data analytics and visualization is right for them. Similar but alternative career and study paths include business analytics, business intelligence, operations research, and computer science.

Or perhaps you know that this is the field for you, that you were born to interpret data and create visualizations that reveal hidden meanings in data sets. If that's the case, dig in: A Master of Science in Data Analytics and Visualization may really be right for you.

Questions or feedback? Email editor@noodle.com

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