Data Analytics
Learn to turn raw data into real insight.
- 24MonthsDegree completion timeline
- 100%Online FormatFlexible learning with an interactive weekly class
- 34%Average job growth for careers focused on data analysis*
- $112ThousandMedian earnings for data analytics professional with graduate degree**
* U.S. Bureau of Labor Statistics
** research by Appily College Search
Why applied analytics matters:
Data analytics is the universal language almost all organizations speak today — from healthcare and finance to technology, public policy, and beyond. Skilled analysts are in high demand to identify patterns, interpret results, and predict future outcomes that guide strategic decisions. A graduate degree in applied analytics prepares you to not only manage data but to turn it into actionable intelligence that can solve complex problems, inform innovation, and improve outcomes on a global scale.
How a master’s in applied analytics from Muhlenberg can propel you forward:
Muhlenberg’s master’s in applied analytics program is delivered 100% online in small, synchronous classes and can be completed within 24 months. The curriculum blends technical expertise with the ability to tell powerful stories through data, equipping you to find patterns within datasets, create visualizations, and communicate findings to diverse audiences. Team-based projects and real-world case studies ensure you graduate ready to meet the demands of a data-driven world.
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The program provides a strong foundation in statistical analysis, programming, data management, business intelligence, and visualization. Students also explore cloud computing, advanced modeling, and the ethical and regulatory considerations of data work. Courses are designed to integrate technical skills with strategic decision-making, giving graduates the ability to select appropriate tools and models for a variety of professional contexts.
Students put their learning into practice through applied projects in areas such as urban analytics, population health, sustainability, and predictive modeling. These problem-solving contexts simulate real-world challenges and foster collaboration, critical thinking, and innovation. The program culminates in a capstone project that showcases each student’s ability to analyze complex datasets and present actionable insights.
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