Guide to a Master’s Degree in Data Analytics

By Kat Campise, Data Scientist, Ph.D.

One of the most popular career paths for new data professionals is a role in data analytics. This booming profession is of growing importance in industries of all types, from government agencies to health insurance companies to mass-market retailers, making it an especially promising area of big data to choose as a concentration.

So what do data analysts do?

Put simply, data analysts are the collectors and preliminary processors of all incoming datasets a company captures.

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Data analyst salary and job growth statistics

For those who are keen on finding a career path that promises to be both lucrative and stable, a data analyst job will surely fit the bill. Data analysts are certainly part of the big data boom that has led to the rapid proliferation of jobs in all sorts of industries in cities all over the country. In recent years, many data analyst opportunities are remote as well, making it even easier to jumpstart your career from wherever you are.

Indeed, the job growth predictions for data analysts are strikingly positive, vastly outpacing most other industries. The Bureau of Labor Statistics projects a stellar growth rate of 23%, a number significantly higher than most occupations outside of the other data science professions. If you are interested in focusing within mathematical science operations, the job growth projections are even higher, coming in at a whopping 29%.

Because data analysts are so in demand and provide such valuable skills, they are well compensated for their work. The Bureau of Labor Statistics finds that the median annual salary for operations research analysts is $82,360 per year, with the median numbers in more specialized industries reaching six figures.

With this salary range and job growth expectancy, it’s easy to justify the investment of a data science master’s program, as it promises to lead to a career that will continue to thrive for years to come.

The first step toward pursuing a career in data analytics is obtaining your master’s degree. This is for all intents and purposes a prerequisite to enter the field in a competitive position, instantly asserting that you have the skills and insights needed to handle a data scientist’s complex responsibilities.

Most students who pursue Master’s in Data Analytics degrees come from a background in computer science, calculus, or statistics, though there is no formal requirement for your bachelor’s degree. However, it is crucial to build fluency in a programming language such as Python or Java as well as core competencies in calculus and advanced mathematics before taking on the advanced coursework of a master’s program.

If you are ready to take the next steps toward pursuing a master’s degree in data analytics and are specifically interested in in-person educational opportunities, this guide will tell you everything you need to know about how to choose the right program for you.

For information about online master’s degree programs, take a look at our guide here.

In This Guide

Step 1 – Select a Career Trajectory
Step 2 – Research Location and Housing Availability
Step 3 – Compare Costs with Online Options
Step 4 – Determine Timeline
Step 5 – Analyze Curriculum and Admissions Process
Step 6 – Review Schools Offering a Master’s in Data Analytics

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Steps to Choosing an On-Campus Master’s in Data Analytics Program

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.

data science career trajectory

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.

data science job

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
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 focusing on an analytics career trajectory. Thus, select an on-campus Master’s Degree in Data Analytics program that you find most compelling.

Step 6: How to Choose an On-Campus Master’s in Data Analytics Program

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.

FAQs

What are the advantages of an on-campus master’s program?
With so many strong online options for data analysts, it’s fair to wonder why one might prefer to attend an in-person program. The answer is simple: resources. While students in online degree programs will still receive a complete education that will make them competitive candidates for top data analytics positions, attending school in person provides better access to mentorship, a community of fellow students, opportunities for networking, and even news of potential internships. If you have the option to attend an in-person master’s program, these advantages are worth considering seriously.

Are there good master’s programs in states that don’t have large data science industries?
Yes. As you will see in the list below, there are excellent data analytics programs all over the US, not all of them located in major tech industry hubs. In fact, beyond simply where you attend graduate school, there are great reasons to consider pursuing a career in data analytics outside of the national hubs for data science (such as Silicon Valley), as nowadays businesses of all types have a need for data analysts. Some shrewd data analysts have capitalized on this, focusing on areas of data analytics where there are big opportunities with less competition.

What type of work will a data analytics degree allow me to pursue?
As mentioned above, data analytics is a particular field that requires its own specific skill set. It is a different approach from other areas of big data, such as data science, cybersecurity, or business intelligence (BI). This means it’s crucial to be sure that this is the right area for you before taking on your master’s program, as it will leave you with skills that are related to other areas of data science but refined around analytics specifically.

Why get a master’s degree instead of completing a certificate program?
While there are excellent certificate programs out there to help working data analysts build up further areas of specialization, only a master’s degree will make you a competitive candidate for top data analytics positions. Certificate programs tend to be focused on individual skills or topics that can be useful to know, but prospective employers will want to be assured that you have the full breadth of knowledge that a master’s program confers. If you’re looking to start a lasting, high-earning career, a master’s program is your best bet.

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School Listings for a Master’s Degree in Data Analytics

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
2022-2023 Tuition: $1,866 per credit

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