Humans create a staggering amount of data every day, and these numbers only continue to increase over time. In the last two years alone, for instance, we’ve generated more data than ever existed before, which has subsequently led to the use of this available data in many facets of business, government, and more.
This increased reliance on data across industries for decision-making has also created a growing demand for professionals with the knowledge and practical skills needed to interpret, analyze, and present data in a way that is concise, efficient, and impactful.
However, this unique combination of knowledge and skills often cannot be obtained with only a bachelor’s degree. To achieve the level of understanding needed to succeed in this demanding field, many professionals who desire a high-paying career in analytics choose to pursue a master’s degree.
Is a Master’s in Analytics Worth It?
Although it may seem daunting to go back to graduate school as an adult, research shows that obtaining a master’s degree in your field can benefit your career in a variety of ways. From increased salary potential to opportunities for promotions to a chance to expand your professional network, the impact of this investment is limitless.
For data analysts, these benefits are even more substantial. Read on to learn about the ways your analytics career can benefit from a master’s degree.
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The Benefits of a Master’s in Analytics
1. Increased Job Opportunities
It’s not difficult to appreciate how promising the career outlook for data professionals is today. Even at a quick glance, we learn that:
- By 2022, 85 percent of companies will have adopted big data and analytics technologies, and 96 percent of companies plan to hire new permanent staff with relevant skills to fill future big data and analytics-related roles.
- In their list of the top jobs in America, Glassdoor has named careers in data science number one four years in a row.
- The U.S. Chamber of Commerce and Burning Glass Technologies report that the supply of analysts has not been able to keep up with the growing demand for their skills in workplaces today.
With the unlimited career potential for those in data-related roles, it’s no wonder so many are hoping to land a job within this coveted field. However, in order to stand out among other candidates, research shows that job applicants with a master’s degree have credentials and experiences that set them apart during an interview, as compared to those applicants with only a bachelor’s.
Randy Bartlett of Blue Sigma Analytics adds that twenty-five percent of hiring teams for data analysts specifically “prefer or require candidates to have a graduate degree, making an advanced credential increasingly important if you want to stand out and be competitive.”
2. Advanced Skills & Hands-On Experience
Employers favor candidates with master’s degrees for several reasons; the pursuit of an advanced degree exemplifies how serious the applicant takes their work, and it also demonstrates their commitment to lifelong learning.
The most significant message that a master’s degree sends to an employer, however, is that the candidate has taken the necessary steps to obtain the practical skills and experiences they will need in order to succeed in this demanding industry.
“The objective of an analytics degree should be to teach the skills that will allow an analyst to ‘illuminate’ the world around us—to effectively communicate and lead with data-driven insights, and therefore mitigate risk in the decision-making process,” Bartlett says.
Individuals who participate in programs like Northeastern’s Master of Professional Studies in Analytics graduate having had the opportunity to not only learn from working professionals in the industry but to also practice their skills through a variety of hands-on experiential learning opportunities within one of the well-known organizations that make up Northeastern’s expansive network.
“[Northeastern’s] program helps students establish confidence in their abilities to master analytics at the intersection of technology and business application,” Bartlett says. “Through [these] experiential learning opportunities, students gain hands-on experience and an understanding of the true power of analytics.”
What’s more, courses within this program focus on developing students’ “soft skills” alongside the more tactical ones. These skills include communication, creativity, presentational abilities, project management, problem-solving, and leadership, among others, and are now considered necessary skills for success in a data science career.
3. Knowledge of Emerging Industry Trends
As technology continues to improve and develop, and the applications for data-related insights across industries continue to expand, the skills that are required for success in the industry will also continue to change. In order to remain relevant, data professionals must stay abreast of emerging trends and develop the necessary skills to address them.
One currently evolving trend is the application of Artificial Intelligence (AI) in data analytics. “While AI disrupts numerous professions—in a good way—analytics skills will become increasingly relevant in a world with more automation and statistics-based decision making,” Bartlett explains.
Master’s programs like Northeastern’s provide the necessary insights and tools needed for aspiring analysts to stay on top of these (and similar) trends in order to have a competitive advantage in the job market. The program offers an entire concentration on statistical modeling, for example, which covers relevant topics such as predictive analytics and data mining applications.
Northeastern’s Commitment to These Changing Trends
This approach to AI and other evolving digital trends is not unique to Northeastern’s data analytics programs, however. The entire university is dedicated to developing students with the knowledge and skills to embrace these technologies and use them to benefit their work. Northeastern’s academic plan states:
“Northeastern is perfectly positioned to lead a revolution in higher education that ensures the era of intelligent machines is one of expanding opportunity. An evolution based on networks: networks for lifelong learning and discovery that make people more agile, adaptable, and creative, and inspire us to be fully human.”
Although the increased reliance on AI and machine learning is only a single trend, it offers a perfect example of how those who enroll in a graduate program have the opportunity to address these changes and learn how to best adapt, all while under the guidance of industry professionals.
What makes up a good master’s in data analytics program?
For those who have internalized the benefits of a master’s degree in analytics and are ready to enroll, Bartlett emphasizes that there are a few key elements to consider before choosing a program. Below, we explore these elements and the impact they can have on a data professional’s education.
Element #1: A Balanced Curriculum
According to Bartlett, a master’s in analytics program should “deliver on how to extract and manipulate data, transform that data into information, and then [turn] that information into insights.” He identifies that, alongside an advanced grasp of “soft skills,” the programs that best prepare students for these processes are focused on providing a balanced, advanced understanding of both computer science and statistics practices specifically.
Although these two facets of data analytics should be explored equally, he insists that effective programs will place a different type of emphasis on each. Computer science training, for example, should remain practical, while the “depth of statistics training must be dense enough to support future growth.”
Bartlett goes on to list out some of the top tactical skills and concepts that should be covered within each component of the program. From a computer science perspective, students should learn about:
- Programming techniques
- Creating and maintaining databases
- Working with computer hardware
- Welding new, advanced software for problem-solving
The statistics content covered within the program, on the other hand, should include practice in:
- Identifying statistics problems
- Figuring out underlying assumptions of those problems
- Making analytics-based decisions
- Solving a problem using software or identifying a specialist who can
Students that graduate with a combination of these vital industry skills will be more easily able to translate what they have learned to the variety of data roles that need to be filled.
Element #2: A Customizable Education
A top data analytics graduate program will allow students to not only obtain the fundamental skills they need to succeed, but will also offer students the option to tailor the curriculum to align with their personal areas of interest, as well as their location and learning style.
Northeastern’s Master’s of Professional Studies in Analytics program allows students to tailor their studies through the declaration of an industry-aligned concentration. Currently, these three specializations include:
- Statistical Modeling
- Evidence-Based Management
- Informational Design
Students also have many opportunities to further customize their course load by handpicking three electives from a list of 35 exciting courses with titles such as “Leadership in Analytics,” “Data Warehousing and SQL,” “Advanced Spatial Analysis,” “Ethical Leadership” and more.
Customized Learning Styles
For many students, one of the main concerns when returning to graduate school is the time commitment. Luckily, institutions like Northeastern have come to develop programs that can be completed part-time or full-time, and via on-ground, online, or hybrid formats, depending on the student’s preferences and availability.
Northeastern’s MPS in Analytics program, for example, is offered in both part-time and full-time capacities. Classes can be taken fully online, on-ground in Boston, or on-ground at one of Northeastern’s notable regional locations, including Seattle and Silicon Valley.
There are benefits to online or regional programs that extend beyond flexibility, however. For example, analytics is one of the top three industries in the San Francisco Bay Area, making the choice to pursue a master’s in Silicon Valley a strategic move for students looking for ample career opportunities after graduation.
Element #3: Ties to Real-World Experience
Bartlett finds that a program’s emphasis on real-world experience is a significant indicator of its students’ success. Although this type of experience can take many shapes and forms, he identifies the faculty’s ties to the professional world and the opportunities for hands-on learning offered to students among the most telling aspects of a program’s potential.
Faculty with Industry Experience
“Teaching should be more about imparting wisdom—and invaluable wisdom is learned in the field,” Bartlett says. “To find a strong master’s of analytics program, [students] should look for a faculty with professionals who have real industry experience, like those at Northeastern.”
Although this may seem like a given, Bartlett stresses that learning from individuals who have current industry knowledge is the only way students can stay on top of the changing trends in this field, and graduate ready to face those challenges head-on.
Hands-On Learning Opportunities
He also considers the opportunities students are given to actually practice what they learn in the classroom in the professional world to be directly correlated with those students’ success.
“[A] master’s degree should include professional training, which is invaluable early in your career,” he says. “The right training will accelerate [students’] command of these advanced topics and provide a foundation for continued growth and lifelong learning.”
Northeastern’s master’s in analytics program not only encourages experiential learning among students, but requires it. Through an experiential capstone course, each and every student is given the opportunity to go into an active work environment and apply the skills that they’ve learned to real-life scenarios. This system provides an unparalleled opportunity for these students to test out their understanding of these advanced topics and practices, while still having a network of professors and classmates to rely on for guidance and insight if needed.
“After earning your master’s degree in analytics, you should be able to think statistically and use today’s emerging software, while possessing a degree of professional acumen,” Bartlett says. “Choosing the right [program] can prepare you for a future of growing job opportunities and help you advance your career.”
To learn more about advancing your career in analytics, download our free guide below.
This post was originally published in September 2017. It has since been updated for accuracy and relevance.
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