Guide to a Master’s Degree in Data Analytics

The differences between an on-campus Master’s Degree in Data Analytics and the online version are quickly disappearing. Other than having to navigate travel time to the university, and sitting in a traditional classroom, there is only a slight disparity that favors in-person degree programs. For example, many universities have a health fee incorporated into the student fees, which means that students have access to the on-campus health office for flu shots (and even dental work, if available). Need graduate student housing? Maybe you’ve had a particularly stressful semester and feel the need to speak with a mental health counselor? Such offerings are frequently provided by universities for their on-campus students throughout the U.S. However, the overall quality of the two program types, online vs. on-campus, is virtually identical.

Choosing an on-campus Master’s Degree in Data Analytics isn’t drastically different from an online program. For most programs, you’ll be expected to have a fundamental understanding of statistics (at least undergraduate level knowledge), and likely need to have some experience with SQL along with other analytical tools, e.g., SPSS, SAS, PowerBI. Granted, certain Master’s Degree in Data Analytics programs may introduce you to analytical software that is commonly used within the business world. Moreover, depending on how employers classify their data analytics employees — larger enterprises and government entities may have Data Analyst I, II, III designations, each with increasing levels of technical and statistical requirements — you may be expected to know R, Python, and machine learning.

Usually, hardcore statistical programming and developing predictive models are reserved for data scientists and machine learning engineers. Nonetheless, analytics degrees at the master’s level are increasingly conflating data science and data analytics (data scientists are indeed analysts, but they possess an in-depth knowledge of math, statistics, a great deal of programming knowledge and application, as well as business domain expertise). This point leads us to the first step in the degree program decision process.

Step 1: Select a career trajectory

Is your ideal day toiling away with analyzing a specific business problem, developing a hypothesis, data collection, cleaning, preprocessing, exploratory data analysis, and building predictive analytics models? Do you enjoy math, statistics, and codifying the solution to a specific business problem by translating it into R or Python? (Note: for predictive models that will be launched into a larger software production framework, it’s likely you’ll be using Python — for now.) If so, then a Master’s in Data Analytics can be your first step toward data science. Yes, there are Master’s Degrees in Data Science. But, an on-campus Master’s Degree in Data Analytics can also lead you in that same direction (make sure that you’re developing or have developed the data science skills discussed above; some of the degree programs in data science and analytics are nearly identical).

Yet another consideration is your target industry. Analysts of all sorts are needed in every single industry: manufacturing, marketing, public health, agriculture, medicine, law (text analytics), education, government, cyber security, supply chains, finance, and the list goes on almost ad infinitum. There are many career options within the analytics field: data analyst, business analyst, IT analyst, marketing analyst, systems analyst, etc. But, research each one that you’re considering as they may require additional education and/or certifications in addition to your graduate degree.

Also, another sidenote is warranted: there will likely be aspects of data analytics that don’t absolutely thrill you on a daily basis. For example, in a data science context, not every data scientist enjoys cleaning and preprocessing data (which can consume up to 80% of a data scientists time — that is, until new tech solutions come along). This fact does not mean that data analytics isn’t the right fit for you.

Step 2: Research the university’s location and housing availability

If you’re planning on attending a local university, then this step might not apply to you other than driving time, traffic, and parking logistics. For those who do not have a nearby university that offers an on-campus Master’s Degree in Data Analytics, this becomes a more important phase of the decision-making process.

While the quality of the program definitely matters, having to move to a new city requires additional planning and, of course, money. Does the university have graduate housing? If so, what is the application process? What costs are involved? Is family housing available (for graduate students with children)? Off-campus housing may be easier to obtain, depending on the city. Either way, you’ll need to consider the university’s location and whether it’s feasible both financially and logistically. At this step, it’s recommended that you narrow your university list down to between three and five choices, which will be further reduced if you have constraints on where you’re willing to move to (or travel to).

Step 3: Compare the costs of an online vs. an on-campus Master’s Degree in Data Analytics

After years of private, for-profit schools dominating the online degree program world, Ivy League schools are now catching up. It may be more financially feasible for you to choose an online Masters in Data Analytics from an Ivy League university as opposed to shouldering the additional costs associated with an on-campus degree program. Many online programs are, overall, less expensive than their on-campus counterparts. If you’re totally committed to completing an on-campus program, and you’ve already decided that the location is doable with regard to travel and living expenses, then determine how much more you might be spending for an on-campus Master’s Degree in Data Analytics. Also, if you still have more than one on-campus program on your university list, compare their total costs as well.

One more consideration associated with a program’s cost is what the on-campus experience provides in terms of additional benefits. Does the university have job placement available? Do they incorporate employer sponsors where you’ll be working on actual, rather than theoretical, business problems in collaboration with a possible future employer? What percentage of graduates land a job after completing the degree? Granted, a student can obtain a stellar Masters in Analytics degree from one of the top programs in the world and still not be able to land a job. But, there are individual factors in that equation which impact the outcome of their job seeking and universities have no control over those aspects.

Step 4: Determine the degree program’s length

There’s no hard and fast rule that on-campus Masters in Analytics programs are longer than the online version. However, on-campus programs are more likely to be tethered to the usual semester-based structure. As such, this may extend the length of your program as you are required to complete the usual X number of credits per semester. Additionally, summer courses may or may not be available.

Consequently, an 18-month online program might equate to a 24-month program (or longer) for on-campus students. Some students welcome a summer break so they can regroup. Others may want to simply achieve a Data Analytics Master’s Degree as quickly and efficiently as possible. So, in addition to a cost comparison at the tuition and fee levels, a time comparative is in order. Ultimately, the longer your on-campus degree program takes for completion then more financial outlay will be required due to travel expenditures.

Step 5: Analyze the curriculum and admissions process

The curriculum and admissions process is another area where universities tend to differ — with one caveat: if you’re an international student, you’ll likely need to prove your English proficiency by passing the IELTS or TOEFL exams. Beyond that requirement, some Master’s Degree in Analytics programs may waive their GRE or GMAT admissions prerequisites. If the universities on your list still require the aforementioned exams, then plan to spend roughly $300 or more for testing fees and study materials. Most, if not all, universities also expect that you’ll provide a brief statement of purpose and letters of recommendation from prior educators and/or employers.

When it comes to curriculum differentials, there is an essential set of coursework that tends to repeat regardless of the university: SQL, statistics, and specific analytic software programs. A growing number of programs go a step further and require a programming language, usually Python. From there, curricular divergence occurs as a Master’s Degree in Analytics can take many forms: business analytics, data analytics, system analytics, etc. Then you’ll need to consider the elective courses that are available such as data mining, cybersecurity, analyzing social media, text analytics, and so forth. This step circles back around to the first step where you’re focussing on an analytics career trajectory. Thus, select an on-campus Master’s Degree in Data Analytics program that you find most compelling.

Step 6: Choose a university and apply

By this step in the decision process, you may have already eliminated the other universities on your list and are now down to one choice. This is particularly true if you have location limits on where you’re willing to move and/or how much travel time you can tolerate. If the university you have chosen has the same admission requirements when compared to a particular dream school, along with an equally interesting curriculum, then you may want to send an application to both. A degree from an Ivy League university still holds a great deal of “sway” when it comes to potential employers and moving past the Human Resource departmental gatekeepers. Alternatively, applying to both online and on-campus Master’s Degrees in Data Analytics increases your chances of entering a program that best fits your timeline and cost.

School Listings

American University– Washington, D.C.
Master of Science in Analytics (MSAn)
Students in American University’s Master of Science in Analytics program will partner with a local organization to work through and solve analytics problems which are integral to the company’s operation. The capstone of the program connects theory with practice, giving students the real-world skills needed to succeed. Overall, the MSAn prepares students to be experts in the field of data analysis with the knowledge to study and utilize data in a variety of organizational and business challenges.

Program Length: 33 Credits
Delivery Method: Campus
GRE: Required or GMAT
Tuition:$1,708 per credit
Course Offerings

Bowling Green State University– Bowling Green, Ohio
MS in Analytics
Bowling Green State University’s MS in Analytics fulfills the job markets strong need for experts in data analysis to study the wants and needs of the explosion of modern computing technology. The MS in Analytics program endures for 12 months in a full-time, cohort format. Students work in a hands-on environment with descriptive, predictive, and prescriptive analysis methods. Students learn technical skills in database management, business intelligence, and big data analysis, as well as skills in management and leadership.

Program Length: 33 credits
Delivery Method: Campus
GRE: Required or GMAT
2018-2019 Tuition: $435 (Ohio resident), $748.50 (Non-resident)
Course Offerings

Canisius College– Buffalo, New York
Data Analytics M.S.
Through the College of Arts & Sciences, the Data Analysis M.S. at Canisius College prepares students to be data analyst specialists across a wide variety of industries along with teamwork and communication skills essential to working in diverse, multidisciplinary organizations. Highlighted courses include Data Stewardship, Data Mining and Machine Learning, as well as Visualization and Presentations of Advanced Analytics. This is a 1-year program with 15 to 20-student classes, part-time options, and strong industry connections that will lead to internships and job acquisition.

Program Length: 30 credits
Delivery Method: Campus
GRE: Not Required
2018-2019 Tuition: $820 per credit
Course Offerings

Central Michigan University– Mount Pleasant, Michigan
Master of Science in Applied Statistics and Analytics
Students at Central Michigan University in the Master of Science in Applied Statistics and Analytics program study one-on-one with faculty in risk analysis, Bayesian techniques, and data mining. The 2-year program works well with students aiming for advanced careers in statistics and data analytics. Most courses in this program require a semester-long research project, which is then exhibited at the annual poster presentation. Students have the opportunity to compete at an international level through SAS Inc.

Program Length: 30-36 credits
Delivery Method: Campus
GRE: Required
2018-2019 Tuition: $417 per credit (Michigan Resident), $789 per credit (Non-resident)
Course Offerings

Capella University– Minneapolis, Minnesota
Master of Science in Analytics
Capella’s online Master of Science in Analytics program consists of 11 core courses with a capstone and a virtual internship. Students take 1 to 3 courses per 10-week quarter with weekly assignments and courseroom discussions. Tuition rates vary by student, as they pay for what they take and prices vary by the courseload and term. The program enhances skills in data mining, statistics, applied analytics, modeling, forecasting, and interpreting.

Program Length: 32 credits
Delivery Method: Campus or Online
GRE: Not Required
2018-2019 Tuition: $33,360 total
Course Offerings

Fordham University– New York City, New York
M.S. in Data Analytics
Not only do students learn to analyze and manipulate large sets of data, they also gain in-depth knowledge in at least one area of specialization. Students also have the opportunity to take electives in economics and urban studies. The curriculum requires 10 courses, including 4 core courses, 2 advanced knowledge courses, 3 electives, and a capstone project or thesis. This is a 1- to 2-year program with evening course options to accommodate working professionals.

Program Length: 30 credits
Delivery Method: Campus
GRE: Required
2018-2019 Tuition: $1,261 per credit
Course Offerings

Georgia State University– Atlanta, Georgia
M.S. in Data Analytics
Students will learn to solve problems that truly matter in the world of data analytics. For example, students will detect fraud via image recognition with Georgia-Pacific, determine what website behavior leads to a sale with SunTrust Banks, or predict client attraction through text mining with SunTrust Banks. The M.S. in Data Analytics program is customizable to each student with evening courses, 4-week math foundations courses for students in need of additional prerequisites, and tech business connections for international students who are new to Atlanta.

Program Length: 30 credits
Delivery Method: Campus
GRE: Required
2018-2019 Tuition:  $39,000 total (Georgia residents), $44,000 total (non-Georgia residents)
Course Offerings

Kansas State University– Manhattan, Kansas
Master of Science in Data Analytics
The College of Business has partnered with 6 departments across campus to offer a competitive graduate program that covers data science, analysis skills, and business management. The program encourages community engagement and research projects, so students are actively practicing hands-on analysis skills. Students take 30 hours of coursework with a choice of the Data Science Track or Applied Analytics track.

Program Length: 30 credits
Delivery Method: Campus
GRE: Required
2018-2019 Tuition:  $419.20 per credit hour (resident), $946.20 per credit hour (non-resident)
Course Offerings

Maryville, University– St. Louis, Missouri
Master of Science in Applied Statistics and Data Analytics
This 12-course program offers 5 required courses, 10 elective options, and 5 other elective course options. To deal with big data, students will make proper statistical inferences, develop statistical models for use in business situations, use statistical tools to manage risk, and make professional judgments based on sound ethical values. All Maryville University Mathematical Modeling and Actuarial Science undergraduate students in good standing are eligible for early access to the Master’s program in Applied Statistics and Data Analytics.

Program Length: 36 credits
Delivery Method: Campus
GRE: Not Required
2018-2019 Tuition:  $797 per credit
Course Offerings

New England College– Henniker, New Hampshire
Master of Science in Data Analytics and Business Statistics
Students with a bachelor’s degree wishing to prepare for a career in the emerging global opportunities in data analytics should apply to the Master of Science in Data Analytics and Business Statistics program. The program begins 7 times throughout each year and consists of 10 classes/40 credits or 10 classes plus an internship for 44 credits. The Internship Track allows students to connect academic study with applied practice so they can better understand the work expectations in an individual organizational culture. Students with F-1 visa status may cooperate with their International Student Advisors for the use of Curricular Practical Training (CPT).

Program Length: 40 credits
Delivery Method: Campus
GRE: Not Required
2018-2019 Tuition:  $565 per credit
Course Offerings

North Carolina State University– Raleigh, North Carolina
Master of Science in Analytics
This 10-month cohort-based program is structured for personalized learning that pursues genuine problems provided by industry and government sponsors. Students work in a state-of-the-art facility and the Hunt Library on the Centennial Campus.

Program Length: 30 credits
Delivery Method: Campus
GRE: Not Required
2018-2019 Tuition:  $23,460 total (NC Resident), $43,466 total (Non-Resident)
Course Offerings

Northeastern University– Boston, Massachusetts
Master of Professional Studies in Analytics
Located in Boston, this 2-3 year program includes full-time and part-time options and meets F1 visa requirements. While training for industry jobs, students acquire rigorous analytical skills as well as research experience to prepare for the doctoral program in health, security, and sustainability at Northeastern University, but electives are offered through diverse disciplines for a unique education.

Program Length: 36 credits
Delivery Method: Campus
GRE: Required
2018-2019 Tuition:  $34,200 total
Course Offerings

Northwestern University– Evanston, Illinois
Master of Science in Analytics
At the McCormick School of Engineering, students perform data engineering processes on-premise and in the cloud. After identifying patterns in the data, students apply artificial intelligence solutions to deploy machines to augment human decision-making. Then students communicate their findings in practical and effective terms that help organizations succeed. An internship and industry-supplied projects will solidify all practices.

Program Length: 15 months
Delivery Method: Campus
GRE: Required
2018-2019 Tuition:  $85,000 to $95,000 Total cost
Course Offerings

Penn State Great Valley– Malvern, Pennsylvania
Master of Science in Data Analytics
This 30-credit program combines theories of statistics, computer science, machine learning, and software engineering. With an emphasis on research, this program prepares students for a doctoral program in data analytics. The 5 required courses and 3 electives with 6 credits of supervised research (concluding in a thesis paper) instead of a capstone. Students must complete a thesis defense, and the paper must be accepted by advisers and committee members, the head of the graduate program, and the graduate school.

Program Length: 30 credits
Delivery Method: Campus
GRE: Required
2018-2019 Tuition:  $1,024 per credit
Course Offerings

Pratt Institute– New York City, New York
Data Analytics and Visualization M.S.
This program teaches students to transform massive raw data sets into useful information through methods of statistics, technology, research, and design. Students address a growing need for information on a national level as well as a local level so they can work in a wide range of organizations. Graduates of the program will understand the full lifecycle of data, from data acquisition to manipulation to storage to statistical analysis and interpretation, and finally dissemination of data artifacts through visual and narrative means.

Program Length: 36 credits
Delivery Method: Campus
GRE: Not Required 
2018-2019 Tuition: $1,428 per credit
Course Offerings

St. Louis University– St. Louis, Missouri
Applied Analytics M.S.

Program Length: 36 credits
Delivery Method: Campus
GRE: Required
2018-2019 Tuition: $780 per credit
Course Offerings

St. Thomas University– Miami Gardens, Florida
Master of Science in Big Data Analytics
At St. Thomas University’s Master of Science in Big Data Analytics, students will comprehend data warehousing and mining, information technology, statistical models, predictive analytics, and machine learning. The suggested degree plan can be completed in five 8-week terms from fall to summer.

Program Length: 30 credits
Delivery Method: Campus
GRE: Required
2018-2019 Tuition: $782 per credit
Course Offerings

State University of New York Plattsburgh– Plattsburgh, New York
Data Analytics Master’s Degree
This M.S. program is a strong combination of quantitative coursework and real-world applications. By utilizing current industry tools and methods, students will work in the hands-on, lab-based courses to give graduates a practical, competitive experience. The 10-month cohort-based program progresses through courses with the same group of students from start to finish. In only 3 semesters, students can complete the program based on the suggested course sequence.

Program Length: 30 credits
Delivery Method: Campus
GRE: Required
2018-2019 Tuition: $12,879.50 per Semester (In-state), $18,659.50 per Semester (Out-of-State)
Course Offerings

Tufts University– Medford/Somerville, Boston
Master of Science in Data Analytics
This Master of Science program can be completed in as little as one year with accelerated study or at a student’s personal pace. With its interdisciplinary structure, the program is designed to serve students in a broad range of fields. Students will tailor their course selection based on individual interests and professional goals. The structure of the curriculum includes five key components: Conceptual Foundations of Information and Data (1 course), Analytic and Statistical Foundations (4 courses), Professional Competencies (2 courses), Disciplinary Competencies (2 courses), and a capstone project which will incorporate and demonstrate the knowledge and skills gained throughout the program.

Program Length: 30 credits
Delivery Method: Campus
GRE: Required
2018-2019 Tuition: $51,288 per academic year
Course Offerings

University of Arkansas– Fayetteville, Arkansas
Statistics and Analytics M.S.
As a foundation for pursuing a Ph.D., the Master of Science degree program presents a lucrative courseload aimed at preparing students for a successful career in big data. Students choose from a variety of tracks to pursue their career choices, which include Statistics, Business Analytics, Operations Analytics, Computational Analytics, Ed Stat & Psychometrics, Quantitative Social Science, and BioAnalytics.

Program Length: 30 credits
Delivery Method: Campus
GRE: Required
2018-2019 Tuition: $420.19 per credit(Arkansas Resident), $1,137.57 per credit (Non-resident)
Course Offerings

University of Central Florida– Orlando, Florida
Data Analytics M.S.
Through the College of Engineering and Computer Science, students will gain the knowledge to develop algorithms and computer programs for the discovery of useful information from massive amounts of data. This is a nonthesis or thesis program involves 30 credit hours and a culminating experience project. The Independent Learning Requirement is met with successful completion of a capstone project in Project in Data Analysis.

Program Length: 30 credits
Delivery Method: Campus
GRE: Required
2018-2019 Tuition: $369.65 per credit (In-State), $1,194.05 per credit (Out of State)
Course Offerings

University of Chicago– Chicago, Illinois
Master of Science in Analytics
The Master of Science in Analytics program offers a thorough exploration of data analysis with state-of-the-art data-gathering tools, methods, and analytics. This program is in-person with part-time or full-time options starting in August and February. The part-time option lasts 2 to 3 years while the full-time option lasts 5 to 6 quarters. The course structure includes Stats Bootcamp, 1 or 2 foundational courses, 11 core courses which includes 2 capstone courses, and 2 electives. Typically, students with 2 or more years of work experience are an excellent fit for this program.

Program Length: 13-14 Courses
Delivery Method: Campus
GRE: Preferred 
2018-2019 Tuition:$58,160 Estimated Total Tuition and Fees
Course Offerings

University of Houston- Downtown– Houston, Texas
Master in Data Analytics
Students of this program study 27 credit hours of foundation courses in regression analysis, multivariate analysis, experimental design, nonparametric analysis, statistical modeling, simulation, mathematical theory for data analysis, and statistical computing. In addition, students take 6 credit hours or interdisciplinary application courses in business management, science, criminal justice, education, communication, and social sciences for working in a diverse work environment. In a student’s final semester, students are given a chance to work in internships with partnering businesses, industries, and government agencies. Additionally, although the GRE is required, potential students can apply for a GRE waiver for those who qualify.

Program Length: 36 credits
Delivery Method: Campus
GRE: Required
2018-2019 Tuition: $485.00 per credit (Texas resident) $850.00 per credit (Non-Texas resident)
Course Offerings

University of Maryland– College Park, Maryland
Data Analytics Master’s Degree
This degree program is designed to help career-pursuing students master high-demand business intelligence skills. Students will apply predictive modeling, decision theory, big data analytics, and data visualization to real-world projects from a variety of industries. For the best learning practices, students will manage data analytics projects from conception to delivery.

Program Length: 36 credits
Delivery Method: Campus
GRE: Required
2018-2019 Tuition: $458 per credit (Maryland Resident/In-State), $659 per credit (Out-of-State)
Course Offerings

University of New Hampshire– Durham, New Hampshire
Master of Science in Analytics
In only 11 months, students can complete this full-time, three-semester program (summer, fall, spring) exploring in-depth training in quantitative analysis, reasoning, and critical thinking. The program consists of a cohort design and offers specializations in health, business, and a self-designed focus area.

Program Length: 36 credits
Delivery Method: Campus
GRE: Not Required
2018-2019 Tuition: $800.00  per credit(NH resident), $880.00 per credit (Out-of-State Resident)
Course Offerings

Utah State University– Logan, Utah
Master of Data Analytics
The Master of Data Analytics program integrates Statistics, Management Information Systems, Economics and Finance, and Computer Science. Students may specialize in Management Information Systems, Economics and Finance, or Statistics. In a total of 17 credits, students complete courses in Computational Science, Introduction to R, Statistical Learning and Data Mining, Statistical Visualization, Applied Econometrics, Database Management, and a Capstone Project in Internship in Data Analytics.

Program Length: 33-35 credits
Delivery Method: Campus
GRE: Required
2018-2019 Tuition: $20,215 Minimum Cost (At 33 Credits), $25,064 Maximum Cost (At 34 or 35 Credits)
Course Offerings

Valparaiso University– Valparaiso, Indiana
M.S. in Analytics and Modeling
Valparaiso’s 36-credit program is designed to integrate statistics, databases, and visual imaging. Students will gain experience in Python, R, and SAS. Options include research projects or internships so students may apply their new skills to real-world problems. Students complete 4 required core courses and at least 2 courses in computational applications in science, engineering, or another applied area. Finally, students either complete an internship or research project.

Program Length: 36 credits
Delivery Method: Campus
GRE: Not Required
2018-2019 Tuition: $630 per credit
Course Offerings