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How Long Does It Take to Get a Master’s Degree in Data Analytics?

 

Wondering how long it will take to earn a Master’s in Data Analytics? There’s no set answer. It can take anywhere from 12 to 36 months or more to complete a master’s in data analytics program. 

 

Why the difference in completion time? Several things come into play— completion time depends on the structure of the program, the number of courses taken per term or semester, and whether or not the program offers courses year round or only during the fall, winter, and spring semesters.

 

Testimonial

“Organizations want employees who have acquired the ability to analyze and use data. Companies don’t want to wait for them to be trained.”  — Michael Salé, program director for Stonehill’s Data Analytics Master of Professional Studies Program

 

Masters in Data Analytics Full or Part Time? What’s the Time Difference?

 

If you plan to attend a data analytics program on a full-time basis, the curriculum for a master’s in data analytics is usually completed over 3 or 4 semesters. That means full-time students are usually able to graduate in 12 to 16 months, depending on whether or not a summer break is included in the program. 

 

Some programs offer students the opportunity to complete their degree on a part-time basis. Part-time programs generally take 24 to 36 months or more to complete. The length of time depends on the number of courses taken each semester.

 

Data Analytics Master’s Degree: In-Person, Online, or Hybrid?

 

Gone are the days when Master’s degree programs took place in-person in a classroom. Today, more degree programs than ever are offering using varied formats, from fully online to fully in-person. There are also programs that are designed in a hybrid format combining in-person and online coursework. 

 

If you’re thinking about earning your Master’s in Data Analytics, it’s important to think about how you learn best. Some students do better in a traditional, on-campus setting. They may find it easier to concentrate and enjoy connecting, problem-solving, and networking with other students from a wide range of backgrounds. 

 

Other students prefer online learning. For them, things such as scheduling flexibility (important if students also hold a job or have a busy family life) and decreased commuting time/time saving are important. 

 

Still other students prefer a hybrid format, which combines in-person and online classes. Many times the in-person classes are held on weekends, which allows students to continue working while completing their master’s. 

 

Stonehill’s Data Analytics Master of Professional Studies Degree Program is an example of just such a hybrid program.

 

Testimonial

“One of the things we really wanted to do with the Master’s in Data Analytics program was to make it a close cohort of people. Students share best practices, talk about the challenges they face in their jobs, and share how they’re using the skills they learn in the degree. One of the things students can expect is close relationships with their fellow students and making connections and professional connections that will last a lifetime.”

— Michael Salé , program director for Stonehill’s Data Analytics Master of Professional Studies Program

 

 

Stonehill’s Data Analytics Master of Professional Studies Degree Program

 

The data analytics master’s program at Stonehill is based on a 12-month executive cohort model. Each cohort begins the program together in August. Classes occur over a full calendar year, with graduation taking place the following August. 

 

Courses in the program are delivered using a hybrid model of in-person and online coursework. Students attend weekend residencies approximately once every 3 weeks with less than half of the program’s instructional credit contact hours delivered online. Students also attend a 3-day intensive residency at the start of each semester.

 

Weekend residences begin Friday night.  Students have dinner with faculty and other members of the cohort, before attending an evening class. Saturday begins with a cohort breakfast, followed by morning class, group lunch, and afternoon class. Students return home around 4 or 5 PM.

 

The advantage of this type of model is that students go through the program with the same cohort of people, thereby getting to know each other well. Students discuss best practices, talk about the challenges they face in their jobs, and share how they're putting into practice the skills they learn throughout the program. 

 

SAS Academic Specialization at Stonehill’s Data Analytics Master Program

 

A partnership with SAS, a worldwide leader in analytics software, gives graduate students in Stonehill’s data analytics program a valuable suite of resources and a competitive advantage in the marketplace.

 

SAS has granted Stonehill the ability to award a Tier 3 SAS Academic Specialization as part of the College’s Data Analytics Master of Professional Studies Degree Program. It is the highest level of credential that SAS offers its academic partners.

 

Students who complete the 12-month accelerated program will receive both a master’s degree and this academic specialization, affirming their technical expertise in conducting advanced data analysis in various SAS products.  

 

 Testimonial

“Our students consistently tell us that having SAS skills on their resume or mentioning their work with SAS in the classroom has made a big difference during the hiring process. Preparing our data analytics students for jobs in a data-driven economy is one of our most important missions at Meehan.” — Debra Salvucci, dean of the Meehan School of Business