Data Analytics and Visualization Degree Programs – Guide to Choosing a Program
Not all data is business relevant. However, whether fully or potentially relevant, this fact isn’t always immediately transparent during the data collection process. All enterprises must now manage a multi-channel flow of data. It’s costly to store data that isn’t helping to generate new products and services. One of the main functions of a data analyst is to help “make sense” of and decipher between data that’s useful vs. data that’s idly consuming resources.
While data visualization is innately part of the data analytics cycle (e.g., collecting, cleaning, analyzing, reporting, etc.), some universities have emphasized this component of their degree or certification programs. The differences between a degree in data analytics vs. a degree in data analytics and visualization aren’t substantial. Most, if not all, data analytics curriculums have a data visualization course. For those that don’t, you’ll still learn data visualization best practices within the context of other courses.
Keep in mind, however, that building dashboards and user-friendly data visuals is a must in any business environment. You’re going to need to communicate your analyses to stakeholders that aren’t data-savvy beyond “show me the so what.” Data visualization (or “data viz”) can help streamline decision-making as it more quickly reveals emerging trends. So, data visualization is more than just a collection of visually pleasing histograms, heat maps, and pie charts. It’s also a way to interact with the data throughout the data analytics process.
Data Analytics and Visualization Job Growth
All industries need data analyst and visualization experts: healthcare, tech, manufacturing, energy, etc. Data from multiple sources is now the norm rather than the exception. Sensor data, website traffic, customer transactions (online and in-person), machine diagnostics, when it comes to data entry and exit points, the list is almost endless.
As such, it should be no surprise that job growth for data analysis and visualization is on the rise. Per the Bureau of Labor and Statistics, who categorizes data analysts within Computer Information and Research Scientists, the job outlook is excellent. Through the year 2028, the need for data analysts is expected to grow by 16%.
Additionally, if you earn a degree or certification in data analytics and visualization, you’re not eternally siloed into the data analyst job title. Data scientists, business analysts, operations research analysts, and systems analysts are all (technically) data analysts as well. Each of these constitutes a specialized form of data analysis with data scientists being at the top of the data analysis hierarchy due to their advanced computational and computer science skillset.
As to salary, you can earn between $65,784 to $84,418 per year. Much of your potential earnings as a data analyst depend on where you live and the particular demand within your target industry. A data analyst in New York City tends to earn more than one who resides in a smaller city with fewer businesses. But, with the continuous increase in enterprises hiring remote teams and individuals, it’s possible to earn a New York City salary without the high cost of being a New York City resident.
Do you need a degree in data analytics and visualization? Again, there are dependencies. Do you already have a degree in another field? If so, you can self-study by using datasets that directly relate to your initial degree. There are numerous MOOCs and “data camps” available for coming up to speed on any missing knowledge and skills.
On the other hand, if you have absolutely zero experience with statistics (another must-have for data analysis and visualization) and the other requirements, e.g., SQL, Python, specific databases such as Oracle, MySQL or Microsoft SQL Server, then earning a degree might be the best course of action. Given the time and financial commitment of both certifications and degree programs, it would be wise to choose your academic path conscientiously.
Upskilling your analytic know-how will be required regardless of which career you land in. To remain competitive in today’s employment environment, you’ll need to learn in perpetuity. But, if you want to the maximum return on your academic investment, which can swiftly reach the realm of $40,000 or more (including books, software, and other tools for completing the program), you should plan for versatility.
Ask yourself how the skills you’ll learn during an academic program will be transferrable to other careers down the line. Research job titles that are of interest to you and review the skill requirements. Then compare those requirements to the various degree programs that fit your time commitment availability and financial resources. You’ll be well on your way to building a solid foundation for your current and future career goals.
Certifications in Data Analytics and Visualization
Certifications are meant to give you a short overview of the subject. Whether an undergraduate or graduate offering, these certificates are usually between 12 to 15 units maximum. There are outliers and variations, but essentially you can expect to earn a certificate in roughly 12 months. You don’t necessarily need a certificate in data analytics and visualization. Data analytics, business analytics, predictive analytics, data visualization, and several other options exist.
For example, the University of Washington offers a Certificate in Data Visualization either online or at their Downtown Seattle campus. In about nine months, and over three courses you’ll learn Data Visualization Theory, Data Visualization Presentation, and Decision Making Through Data Visualization. You’ll use the most widely used tools to produce your visualizations: Excel and Tableau. Additionally, you’ll become skilled at recognizing and visually implementing the design of data patterns based on “visual cognition and perception.”
Could you learn the same (or similar) skills in a certificate program with a different title? Yes. If you tend to enjoy graphic design, you’ll use those talents and knowledge in data visualization. Remember, in a business context, you’ll need to present your data to non-data experts. So, if you already work with data or your stats skills are solid (you’ve completed a college-level course in basic statistics), then a data visualization certificate could be a great way to upskill.
Bachelor’s in Data Analytics and Visualization
The increase in degrees and certifications emphasizing data visualization is sending a clear message: analysts need to have intermediate to advanced data visualization skills. New York University (NYU) has recognized this fact and offers a Bachelor of Science in Applied Data Analytics and Visualization. According to NYU, this is a STEM degree. Be prepared to take Calculus, Linear Algebra, Statistical Methods, Networking, and Database Design. These courses are in addition to the usual core requirements from other departments such as English, History, and Social Science.
From a career perspective, the demand for highly trained data analysts is likely to remain elevated for almost a decade. Earning an undergraduate degree in data analytics and visualization, especially with NYU’s curriculum, can definitely lead you to further study at the master’s and doctoral levels. You’ll already have the math requirements to enter a STEM or otherwise math-heavy graduate program. Make sure that you have attained, at least, an intermediate application of SQL and an enterprise database management program before you graduate. Doing so will place you in a better position for employment.
Master’s in Data Analytics and Visualization
As you move up the academic ladder, your options for data analytics and visualization begin to broaden. For those who’ve already earned a STEM bachelor’s degree, earning an advanced degree in statistics, data science or business analytics might be the logical next step.
The Massachusetts Institute of Technology (better known as MIT) has a 12-month Master’s in Business Analytics program that covers machine learning, R, Python, SQL, Julia, data communication, and data privacy. The degree is classified as STEM-designation but is offered through MIT’s Sloan School of Management. So, your focus will be on analytics within a business environment, which can mean anything from analyzing financial data in conjunction with the accounting department or providing a written analysis (white paper, business use case, etc.) of the data you collected during your market research — or marketing research.
Whether your goal is to be self-employed or to be continually employable, having a combination of business knowledge and analytic expertise is a winning strategy.
Ph.D. in Data Analytics and Visualization
Ph.D. programs are designed to produce researchers who plan to stay in academia. It’s true that this approach is changing to some extent. But, for most academic institutions, Ph.D.s are trained for researching, writing, publishing, and teaching.
There are currently no Ph.D. programs for data analytics and visualization. There are, however, Ph.D.s for data science and business analytics. If you choose a data science Ph.D., such as the one via Columbia University, you’ll need to meet the math, statistics, and computer science prerequisites prior to entering the program. Industry data scientists, i.e., those working in industries outside of academia, also need business acumen (or, at minimum, industry knowledge).
Alternatively, the University of Oregon’s Ph.D. in Operations and Business Analytics may be a better match. Although it’s math requirements are still hefty, if you’re interested in moving up the corporate ladder (or creating your own “corporate ladder”), Oregon’s program focuses on business management. You’ll still work with massive amounts of data and sharpen your statistical knowledge while also applying your learning to business systems such as inventory management, supply chains, etc.
Summary
Data visualization is an interdisciplinary field that is quickly growing both in terms of career and educational opportunities. This trend is expected to continue as universities look to offer more robust coursework and even specialized degree programs to support the growth of this field.
