What is the difference between the Master of Data Analytics — including its Base Program and its Big Data Systems Option — and the Master of Science in Data Analytics?
The Master of Data Analytics (MDA) is a professionally focused degree that teaches students to design, implement, and apply data analysis techniques to a broad array of industries that use and analyze high quantities of data to determine trends, construct models, and make strategic decisions. This degree has a practice-oriented capstone and is ideal for those who want to immediately apply what they have learned.
The Master of Data Analytics includes two options:
- The Base Program is geared toward the fundamentals of data analytics, including visualization and prescriptive analytics.
- The Big Data Systems Option focuses on data engineering and the IT systems that provide data to the data analysts.
Through its emphasis on research, the Master of Science (MS) in Data Analytics is designed to prepare students for entry into data analytics doctoral programs. Rather than a capstone course, this program requires six credits of supervised research, culminating in a thesis paper. This program is ideal for those who want to enter a doctoral program, conduct research, or teach.
Most of our students enter the Master of Data Analytics Base Program, preparing to land data analysis roles in professional work environments. Some MDA students choose to specialize with our Big Data Systems Option, pursuing positions working with large-scale databases and data warehousing. Other students are interested in research careers and opt for the MS in Data Analytics.
How many credits are required?
Both the MDA curriculum and MS curriculum are composed of 30 credits. Schedule a meeting with a program representative for more information.
How are data analytics classes delivered?
Flexible, seven-week courses let you balance your busy schedule while still reaping the benefits of once-per-week face-to-face classes, like networking and developing interpersonal skills.
How long will it take me to graduate with a data analytics degree?
The choice is yours! We provide flexibility for students, many of whom may be using tuition benefits from their employer or financing their studies on their own. The average completion of a degree program is between two and a half to three years when pursued on a part-time basis, and up to two years if pursued full time.
You can take up to eight years to complete a degree program, and up to three years to complete a graduate certificate.
Are the data analytics programs STEM designated?
Both programs are STEM designated, allowing 36 months total of Optional Practical Training (OPT), compared to 12 months for non-STEM degrees.
Does it matter if I don’t have an engineering or technology undergraduate degree?
Data analytics students usually have undergraduate backgrounds in quantitative fields such as IT, engineering, business, or math, with at least one semester of college-level statistics or probabilities. While there is no work experience requirement for admission, students are often employed in industries such as business, computer science, finance, healthcare, or pharmaceuticals.
If you don’t have a technical background, we offer low-cost, non-credit online prep modules that provide a strong practical foundation. Based on your academic experience, program advisors will recommend the most suitable modules for you.
What scholarships and funding options are offered for data analytics students?
There are a variety of scholarships available to half-time and full-time students who meet certain criteria.
Do the data analytics programs offer experiential learning?
Yes, our instruction and facilitation lean heavily on active and experiential learning techniques. Problems assigned in our courses use real-world datasets from companies and organizations, social media scraping, or government agencies (like NIH, DoT, Veterans Affairs, etc.). Students must address real business, social, or technical problems with these datasets using industry-standard toolsets, evaluate both their approach and outcomes, and reflect on the efficacy of their methodologies and solutions.
Do you allow students to transfer credits into the data analytics graduate programs?
A maximum of 10 graduate credits earned at another accredited institution may be applied. Courses must have been completed, with a grade of B or better, within five years prior to the date of enrollment. Up to 15 transfer credits from Penn State non-degree and graduate certificate courses can be applied to a degree program. Transfer credit approval is granted by the student's academic adviser and division head after an admission offer has been accepted.
What career services are offered for data analytics graduate students?
Our Career Services office provides one-on-one career advancement support, internship guidance, access to career fairs and other career events with local and national companies, as well as an array of other services. An additional perk of being part of the Penn State family is access to career services for life.
Are GMAT or GRE required?
The MS program requires applicants to submit official GMAT or GRE results. These scores are not required for admission to either option within the MDA program.
Are there program metrics?
The J. Jeffrey and Ann Marie Fox Graduate School provides data analytics program metrics on admission data, GMAT/GRE scores, enrollment, student demographics, time to degree, and degree conferral.
