Online Master’s in Data Analytics – Guide to Choosing a Program

If you are considering pursuing a career in data science and are looking into the many professional tracks available in the field, it’s likely you’ve seen data analyst listed as one possible option. This is one of the most popular big data professions out there, and is also one of the most sought after, as data analysts are valuable to a huge range of businesses.

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What does a data analyst do?

So what do data analysts do, and how are they different from other data scientists? In short, the key functions of data analysts are the following:

Collect and process all incoming datasets that a company captures
Evaluate datasets to find insights and identify problems
Convey key findings to company leadership

“Processing” here means safeguarding and storing this data. Evaluating these datasets means analyzing them using statistical analysis models that evaluate a variety of aspects of a business’ operations, from the efficacy of its distribution model to the behavior of its customers. As more and more businesses rely on data to make important decisions about their companies’ futures, these insights can be crucial to informing a business’ strategy. This is where the last part of data analysts’ job comes into play: data analysts often participate in translating their findings to business leadership and stakeholders who may not have the data science background to comprehend the information on its own.

It’s important to note that given the wide range of businesses making use of data analysts, this role can vary greatly in different organizations. However, this is good news for prospective data analysts, as it’s an indication that there will always be job openings for your skill set.

For information about the difference between data analysts and data scientists, visit our guide here.

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Work With Data, Mathematics, and Statistics

If you enjoy working with data to analyze trends via business intelligence (BI) or other analytical software programs — but you aren’t interested in building machine learning models — then data analytics is likely the career path for you. As the field evolves, the aforementioned building of machine learning models may become a requirement of certain data analytics jobs. But, as of now, that domain is still relegated to the field of data science and machine learning engineers.

For data analyst jobs you’ll still need a solid background in both math and, more specifically, statistics. While there are plenty of statistical analysis and BI programs on the market (e.g., SPSS, SAS, Tableau, Microsoft Power BI, etc.), you should understand the what, why, and how of the underlying statistical algorithms used for analysis. Indeed, the more skill you have in math and statistics, the more likely you’ll be viewed as a prime candidate by employers. Eventually, this may lead you to secure a job as a data scientist — if that is your goal.

Data Analyst Salary and Job Growth Statistics

One of the leading factors drawing so many people to pursue work in the data sciences is the exceptional pay rate and job growth predictions for the field overall, which considerably outrank the majority of other industries. This is certainly true for data analysts, who are valuable to companies in a huge range of industries, including Business Intelligence (BI), IT, finance, healthcare, entertainment, retail, and more.

Because data analysts provide such valuable services to businesses, they are remunerated well for their work. According to the Bureau of Labor Statistics, operations research analysts earn a median annual salary of $82,360 per year, which already surpasses the national average across industries. In many industries, baseline pay for data analysts gets even higher: those working for the federal government earn a median annual salary of $120,950, while those in scientific services, manufacturing, and company management earn median annual salaries in the range of $94,070 – $99,790.

If the highly attractive salaries for data analysts aren’t enough to entice you to the field, the tremendous job growth predictions may seal the deal. The Bureau of Labor Statistics reports an anticipated job outlook of 23%, more than double the average for American occupations overall. Indeed, this is closely linked to the big data boom that is only expected to accelerate over the next decade. These numbers should come as great encouragement to those considering entering the field, as they suggest that data analysts who start their careers now are likely to find great opportunities with high pay for years to come.

Steps to Choosing an Online Master’s in Data Analytics Program

Step 1: Research and Choose an Industry

Some Master’s in Data Analytics candidates may simply enjoy working with massive amounts of data, and this is their most compelling reason for becoming a data analyst. However, as stated above, there are certain fields where more job opportunities will be present.

As a general rule, the finance and insurance industries tend to pay the most in terms of salary. If you have no interest in either of those fields (keep in mind these are intense number crunching sectors — think actuarial science and trying to make precise predictions as to which asset classes are going to move up or down), then perhaps the fields of health care, cybersecurity, manufacturing, education or marketing might be more appealing.

You can shift gears as you move through the Online Master’s Degree in Analytics program. But, ask yourself what you can do workwise, day in and day out, that meets your financial, mental, and work-life balance requirements.

Step 2: Identify Your Timeline

Online Master’s Degrees in Data Analytics vary in length from around 12 to 36 months, depending on the university. Goal setting is a significant factor in being able to remove any distractions that may arise (meaning those within your direct control). Family and current work obligations may require that you choose an extended part-time program. Also, if you don’t currently have the minimum math or statistics requirements for a particular program, then you might need to invest additional time in self-study or taking requisite courses.

Once you’ve completed the degree, there is a high probability that it may take three months or more to land a data analytics job (again, this depends on several factors that are unique to your current employment status and analytical skill level). So, incorporate at least an additional three months — if not longer — into your timeline.

Step 3: Review Curriculum and Create a List of Ideal universities

You can find all types of universities offering an Online Master’s in Data Analytics: Ivy League, state schools, and private for-profit institutions. The truth of the matter is that completing a degree from an Ivy League institution does tend to place you at the top of the employee candidate pile. On the other hand, they aren’t generally as affordable as state school options. There are also Master’s Degrees in Business Analytics and Master’s Degrees in Business Intelligence. Both are analytics degrees, but their specific curriculum will vary.

For example, an Online Master’s in Business Analytics may lean towards being a quantitative MBA through coursework in risk management, consumer behavior, operational finance, and managing disruptive technologies. A Master’s in Business Intelligence might include courses in IT governance, information systems administration and management, and business intelligence in financial modeling.

Most, if not all, of the programs — whether Data Analytics, Analytics, Business Analytics or Business Intelligence — will cover data mining, predictive modeling, advanced statistical methods, and database systems. Additional electives or attaining a dual degree (usually by adding an MBA to the Master’s Degree in Analytics) are options to consider as well. Review the curriculum for each university on your list to determine if the course offerings interest you.

Begin your list with 5 or 6 possible universities. Rank your list beginning with your ideal scenario first. Is cost the most important factor? Or are you seeking the most highly ranked university that offers an Online Master’s in Data Analytics program? Does the curriculum interest you? Is there an option to focus on a specific track, e.g., health analytics, geographic information systems (GIS), cybersecurity?

Here is where you start weighing all of the factors in comparison to one another:

Prestige
Accreditation
How long the program has been offered
Total length of the program
Job placement opportunities (some universities will have you complete a project with an industry partner)

Your rankings may change as you move through step 4.

Step 4: Consider the Total Cost of the Program

When it comes to cost, review this component carefully. Many universities will list the total cost of the program, but you’ll likely pay either per course or per credit. There may also be other “fees” that aren’t included in the total cost listed. Check the university’s tuition page — many of them provide a tuition calculator. Accredited institutions will provide information on loan options, both public and private.

If you are considering the student loan option, it’s wise to do so carefully. The student loan issue continues to plague many graduates. Certainly, by earning a graduate degree in analytics, you’re substantially increasing your ability to obtain an analytics job with a good salary. But, the job opportunities may not be concentrated in your current city — which means you may need to move. Remote work for data analytics is still in its infancy. Most employers want you to be in-house. So, those are additional and highly impactful possibilities to think about when analyzing the total cost above and beyond just the program itself.

Step 5: Determine the Admission Criteria

GRE scores, GMAT scores, essential math and programming courses, statistics coursework, and applications fees are just a few of the possible admission requirements you’ll see for each of the programs below.

Usually, but not always, the more prestigious the school, the more requirements they’ll have you adhere to. Many universities may also ask for academic or employer recommendations.

If you’re not the greatest of standardized test takers (this is, in fact, a real issue with many students), then a program that waives the GRE is probably your best bet — if that option is available. The below list currently has more than ten schools offering a Data Analytics Master’s Online where the GRE is not required.

Should your university list consist of only schools that require the GRE, then this will be additional time and cost that you’ll need to incorporate into your timeline and total program cost.

Students who are not native English speakers may also need to take the IELTS or TOEFL to establish their English language fluency.

Step 6: FAQs

Do I have to get a master’s degree to become a data analyst?
Generally speaking, yes, a master’s degree is necessary to pursue a career in data science. This is because the skills needed to become a data analyst are advanced, and prospective employers will need something to vouch for your abilities. Most full-time data analyst positions require the level of competency gained from a master’s program, so that is what will be expected of you in order to enter the field competitively.

Will I need to pursue further schooling after getting a master’s?
No. A master’s degree is the standard level of education for data analysts. Some students – those who are especially interested in research and have the time to take on even more school – choose to pursue their PhD. in Data Analytics, which typically includes all of the coursework of a data science master’s program with additional testing and a dissertation. To learn more about a Data Analytics PhD., take a look at our guide here.

Why pick an online degree program rather than an in-person option?
Both online and in-person degree programs have their advantages and disadvantages. One great advantage of online degree programs is their convenience. For those who are continuing to work while in school, virtual programs can be the thing that makes it possible to pursue school and a career simultaneously. Many online degree programs provide coursework that is left for you to do on your own time, meaning it is far easier to shape your experience around your schedule.

Online programs can also be hugely convenient if you don’t live in a place where there are in-person options and don’t want to move in order to pursue your degree. Since so much of the work of a Data Analytics Master’s program is done on the computer anyway, this would not be a huge loss in terms of your academic experience.

What is the difference between a data analyst and a data scientist?
The distinctions between data science and data analysis can be hard to understand, but they are different individual tracks through the world of big data and even through advanced degree programs. (To make matters even more confusing, data analysis is frequently a concentration within a Data Science Master’s Degree, but if you choose this as your area of specialty, you will gain the skills to become a data analyst, not a data scientist.)

In short, data analysts typically seek answers to specific pre-designated questions about a business’ operations, while data scientists work with raw data to evaluate what questions it might even answer. In this way, you can see that data scientists arrive earlier in the data-processing timeline than data analysts do. For more complete information on the difference between data analysts and data scientists, take a look at our guide here.

Step 7: How to choose an Online Master’s in Data Analytics Program

Once you’ve established that a particular Online Master’s in Data Analytics program fits all of your criteria, e.g., price/cost, curriculum, length of time, school ranking, admissions requirements, and any other student resources such as job placement, then it’s time to apply.

You might want to follow the same recommendation that is offered to students who are choosing a Bachelor’s Degree program: narrow your school list down to three choices and apply to all three. This is especially critical if you are applying to an Ivy League or highly ranked school as they are widely known for being highly competitive when it comes to student admission rates.

analyzing data on screens

Schools Offering Data Analytics Master’s Programs Online

Boston University– Boston, Massachusetts
Online Master of Science in Computer Information Systems Concentration in Data Analytics

This 40-credit degree program consists of 5 Core Curriculum courses and 5 courses of the Concentration Elective Requirements.

Students of this program will learn to generate effective visual presentations of data and examine concepts and techniques of data mining.

After completing the Intro to Computer Information Systems prerequisite, students can begin classes in Business Data Communication and Networks, Database Design and Implementation for Business, Information Systems Analysis and Design, and Strategy Management.

Program Length: 40 Credits
Delivery Method: Online
GRE: Not Required
2020-2021 Tuition: $905 per credit

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