Master's in Data Analytics

Muhlenberg College's Master's in Data Analytics prepares graduates to go beyond data management and governance and develop the data analytics skills necessary to address various organizational areas. Through a mix of personalized instruction and real-world application, Data Analytics allows leaders to make actionable decisions driven by data.

“Before the program, I felt stuck. Within six months of completing my degree, I was promoted to a role where I lead analytics strategy for my organization. The degree gave me both the technical skills and the confidence to step up.”

About the Program

Muhlenberg College's Master's Degree in Data Analytics is an online, ten-course, two-year program in which professionals develop the necessary data skills to identify patterns, analyze results, and predict future outcomes.

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Fixed Tuition

Each course in the Data Analytics Program costs $824, or $3296 per unit. Please visit our financial aid page for more information.

Total cost of Tuition

Graduate Certificate: $17,000
Master’s in Applied Analytics: $34,000

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100% Online

Muhlenberg's Master's in Data Analytics and graduate certificate are available online.
The programs are fully synchronous, meaning you can participate in real-time classes.
You have the freedom to take classes from anywhere you want.

Muhlenberg's instructors receive specialized training in developing and teaching online courses, meaning you will be able to engage with your peers and professors in meaningful and impactful ways.

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Admissions Requirements

Prospective students must have completed an undergraduate degree at an accredited institution. Students admitted to a graduate program will have the following:

Bachelor’s degree from a regionally accredited institution.
Two years of work experience or, if a senior or recent graduate, professional work experiences through internships, summer work, externships, and projects may be sufficient.
Additional admissions requirements follow the college’s graduate admissions policy.

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Learning Outcomes

Comprehension of database design principles, including schema creation, modeling, validation, cleansing, and enhancing user experience
Proficiency in modern quantitative tools for analysis, data model design, and trend identification
Ability to identify suitable tool applications, create decision-oriented models, handle substantial "big data" through preparation and loading, and demonstrate expertise in predictive modeling, stochastic methods, programming languages, and ethical considerations for data privacy and governance

Meet with an Advisor

Use the link below to schedule a meeting with one of our graduate advisors today!

Schedule Now

Meet Cheri, Analyst at Air Products

Cheri Fager 'G21, has always been driven to improve and is energized by synthesizing data to tell a story. Muhlenberg combined Cher's drive for improvement and passion for learning into the perfect program for her.