Our Guide to Master’s in Data Analytics Programs

Data analytics master’s degrees are great options both for those who are already in data analytics and looking to advance their careers and those working in another field who are looking to transition into a data analytics career.

Career advancement

A data analytics master’s is an excellent way for someone who already has some experience in data analytics to improve their skills and learn the latest industry-leading practices in order to be a more attractive candidate for promotion at their current company or for a more senior role elsewhere. In fact, for these more-senior roles, many companies list a master’s degree as either a required or a preferred qualification in job postings.

Career transition

For someone holding a bachelor’s degree either just out of college or working in a different field, a master’s in data analytics can provide the skills, expertise, and experience needed to land a data analyst job. Some programs require that graduate students arrive with some basic experience in programming, statistics, or other quantitative analysis, but many will provide summer bootcamps or introductory courses to allow students of any background to attend, provided they show aptitude for the course of study and for data analytics.

Data analytics vs. business analytics vs. analytics: What’s the difference?

Those researching data analytics master’s programs and perusing data analyst job descriptions frequently come across the fields of “business analytics” and “analytics” and the roles of “business analyst” and “analyst,” respectively. Taken at face-value, these can seem distinct from data analytics and data analysts.

The truth is, there’s a lot of overlap. “Analytics” is often used as an umbrella term into which both data analytics and business analytics would fall. And the difference between data analytics and business analytics is often more about emphasis than essence. Look deeper into all three and you will see a core set of skills, techniques, and expertise with some weighed more heavily depending on the particular use-case.

The same can be said of “analysts,” “data analysts,” and “business analysts.” Some companies — especially large ones — will distinguish between these, with business analysts focusing more on big picture business goals, data analysts focusing more on day-to-day operations, and analysts falling somewhere in between. Oftentimes, however, they are used synonymously. Importantly, any one of these jobs is available to someone holding a master’s in data analytics.

Below, we’ll dive deeper into these positions and what you can expect to earn in them. If you’re interested to learn more about our thoughts on the distinction between a business analyst and a data analyst, we’ve devoted an entire article to it.

What kinds of jobs are available to those with master’s degrees in data analytics?

Those holding a data analytics master’s degree usually find employment in one of four roles: data analyst, business analyst, business intelligence analyst, or data scientist. We’ll give brief summaries of each below, and you can also check out our article on analytics jobs to see some real-world job descriptions.

Data analyst

A data analyst’s responsibilities center on gathering and preparing data for analysis and analyzing it to extract insights related to operations, a product, or some other initiative. Often, the analyst will communicate their findings to relevant stakeholders using data visualization.

Salary.com estimates the average data analyst salary in the US to be $81,719.

Business analyst

A business analyst’s responsibilities center on collecting, preparing, and analyzing data to yield business insights to inform future business actions.

Salary.com estimates the average business analyst salary in the US to be $79,770.

Business intelligence analyst

A business intelligence analyst’s responsibilities resemble those of a business analyst, but they analyze data not to directly determine future actions, but rather to produce informational reports and dashboards on markets, industries, or business performance.

Salary.com estimates the average business intelligence analyst salary in the US to be $85,278.

Data scientist

A data scientist’s responsibilities overlap with those of a data analyst — collecting, preparing, and analyzing data — but a data scientist is also responsible for ideating and executing new approaches to data analysis of big data sets, often using machine learning.

Salary.com estimates the average data scientist salary in the US to be $139,631. While some with data analytics master’s degrees land in data science jobs, if you’re looking to become a data scientist, you should also check out our guide on data science master’s programs.

What are the prerequisites for master’s-level study in data analytics?

As we noted above, data analytics programs differ in the prerequisites they require for applicants. Some programs will require applicants to have at least rudimentary skills in statistics or programming, while others will instead require applicants to have some work experience. We always recommend checking with each program’s website or admissions office prior to applying to ensure that you are a viable candidate.

For master’s programs, applicants are required to hold a bachelor’s degree at the time of matriculation. Schools will generally ask to see your college transcripts and GPA, as well as proof of English fluency if you’re an international student. Though some programs are loosening their requirements for GRE scores, many will still want to see them. Additional application components typically include a statement of purpose and a personal statement.

While there’s obviously some variation, data analytics master’s students can typically expect to cover the following during their graduate program:

• Computer science skills, including programming with programming languages like SQL, Python, or R

• Statistical methods for data analysis, including regression, optimization, and decision trees, as well as certain machine learning techniques

• Data collection, preparation, and processing policies and procedures, including data mining for big data and data cleaning

• Data visualization practices and tools

• Applications in business, non-profits, or the public sector, sometimes through a capstone project

Central to finding a master’s in data analytics program that works for you is ensuring that the curriculum will help you meet your goals. In the next section, we’ll cover this and other considerations as you look into programs.

What should you look for in a master’s in data analytics program?

Choosing which master’s in data analytics programs to apply to and, ultimately, which one to attend is a big decision. As you make your decision, we recommend focusing on the following factors:

Modality

Increasingly, aspiring data analysts wanting the flexibility to pursue a master’s degree while continuing to work or care for a loved one are finding a way to do so through part-time and/or online programs. These programs can reduce lost income potential and relocation and housing expenditures, which can help make the financial calculation of whether to pursue graduate study much easier. That said, there are still many full-time, in-person programs out there to choose from if you want an on-campus experience.

Program profile

While many programs will have similar curricula, they won’t all emphasize the same things. Some might focus more on machine learning techniques, some data visualization, others business applications. As you research, you want to make sure that a program’s strengths match up with what you want to focus on and where you want to go with your career.

Reputation

A school’s reputation isn’t everything: what matters is the education you get, and you can learn all you need to embark on a successful data analyst career without studying at a big-name school and the big price tag that usually accompanies this. That said, name recognition can help set your resume or application apart from others, plus elite schools often have active alumni networks that can pay dividends down the road. In the end, you’ll need to decide for yourself whether paying up for a school’s reputation is worth it. If you need help deciding, hit up LinkedIn to see where graduates of programs you’re interested in have ended up.

Cost

Like all higher education, master’s study is usually pricey, but it doesn’t need to be exorbitant. In fact, there are lots of public schools offering great programs for a fraction of the price of the elite private universities, especially if you qualify for in-state tuition. As you are considering cost, you should also consider any scholarships or grants you might qualify for, lost potential income, increased earning potential from your education, as well as interest if you take out loans to fund your education.

Career support

An education is the first (or next) step in your data analyst career, but you’ll likely need support to reach your full potential. When researching graduate school, pay attention to the kinds of career support they offer, such as internship opportunities, career offices, alumni networks, or private job boards. You should also check to see if they can provide student outcome information, as this data can provide the best picture of whether the degree offers a worthwhile return on investment.

It’s important to emphasize that there is no single “best” master’s in data analytics program for all the aspiring data analysts out there: each student’s background and needs will determine what is best for them. Accordingly, in our picks we focus on presenting a variety of great programs that we think will deliver lasting value instead of ranking them from best to worst. Unsurprisingly, the factors behind our decisions include:

Reputation: Does the program provide valuable name-recognition?

Curriculum: Does the program offer a curriculum that will help you not just get a job, but excel in it?

Career-readiness: Does the program offer sufficient resources to help its students find a job after graduating? Are graduates getting placed in well-paying jobs?

Modality: Does the program offer different options for study, such as part-time or online opportunities?

Cost: Does a school offer good value for money? Is there a high likelihood of a substantial return on the initial investment?

With that in mind, here are our recommendations:

In this guide, we’ve gone over the basics of data analytics, examined some of the reasons to pursue a data analytics master’s degree and some of the potential job outcomes, given some tips for what to look for in a program, and presented some of our favorites. What’s next?

If you see a program that interests you, we’d recommend clicking through to the program’s website to learn more. If you’re interested in master’s-level study but not ready to pull the trigger, you can instead check out our deep dive on how to determine if a data analytics master’s degree is worth it for you. If you want to learn more about online data analytics opportunities, check out our online-exclusive guide to data analytics master’s programs.