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Are you a working professional or a bachelor’s student with a deep love for data? Seriously thinking about the MS in Data Analytics? Use our guide to find the perfect program. Learn more about the degree, including timelines, typical courses, and internships & capstone projects. Skim through details on admissions requirements, degree costs, and potential specialties. Explore career paths and salary numbers. Or skip ahead to our listings of all the master’s degrees in the country.
What is a Master’s in Data Analytics?
A master’s degree in data analytics (or a closely related field) is a industry-focused, graduate-level program that’s designed to prepare students for a career in data analytics, a pay raise or promotion, or further studies (e.g. PhD). If you’d like to learn more about the role of data analyst, have a look at our glossary of industry terms.
- Career Changers: Some people earn a master’s degree in data analytics after completing an undergraduate degree in another subject (e.g. social sciences, science, math, etc.). These are folks who are trying to break into the field of analytics.
- Ladder Climbers: Others pursue a master’s degree in order to boost their current data analyst skills, impress potential employers, qualify for leadership positions, and/or explore new avenues of interest (e.g. data science, data analytics engineering, etc.).
Have a look at the sample curriculum to get a handle on the typical feel of a master’s program.
How They Work: Master’s in Data Analytics Overview
The standard titles for this degree are the Master of Science (MS) in Data Analytics, Master’s in Data Analytics, or Master of Professional Studies (MPS) in Data Analytics, but there are plenty of other options. Learn which master’s degree is best for your needs.
- 1 Year (Full-Time): On a full-time schedule, you’ll often be tackling core data analytics courses in the first two semesters and sliding into electives during the third semester. Budget for 2-3 courses per semester. In the summer before the degree starts, you may need to tackle prerequisite courses or a preparatory bootcamp (e.g. Python training). The final summer will usually be devoted to an internship or capstone project.
- 1.5-3 Years (Part-Time): On a part-time schedule, you could be taking 1-2 courses per semester. The capstone project or internship will still occur at the end of the degree, but it may be stretched out over two semesters. Part-time programs are designed for working professionals, so talk to the program coordinator about your employment commitments.
Some master’s degrees in data analytics will be offered on a full-time or part-time schedule only; some will be available in both formats.
Core coursework for a master’s degree in data analytics can vary widely! If you browse through the links in our listings, you’ll notice that some degree plans resemble upper division courses in a bachelor’s degree in data analytics. But there are also plenty of programs that tackle more in-depth subjects. For core coursework, you’ll typically be taking ~7-8 courses/21-24 credits.
Standard graduate programs in data analytics tend to focus on the key fundamentals (theory & application). You’ll notice universities drawing on the following courses from the Departments of Computer Science and Mathematics:
- Data Analytics
- Data Visualization
- Applied Statistics
- Data Mining Principles
- Databases & Data Warehouses
- Analytics Programming with R
- Python Programming
- Predictive Analytics
- Ethical Issues in Analytics
However, in a master’s degree that’s targeted at students with some knowledge of the field, you could also encounter courses such as:
- Big Data Analytics
- Introduction to Machine Learning
- Text Analytics, Mining & Sentiment Analysis
- Database Analysis & Design
- Optimization Analytics
- Risk Modeling & Simulation Analytics
- Advanced Applications in Data Analysis
- Advanced Statistical Methods
- Operations Research
- Project Management
Even more advanced programs will explore the intersection of data analytics & related fields, with credits in:
- Machine Learning & Predictive Analytics
- Advanced Data Science Concepts
- Data Engineering Platforms for Analytics
- Big Data Platforms
- Time Series Analysis & Forecasting
Concentrations, Minors & Electives
With an MS in Data Analytics, you’ll often be able to choose 2-3 electives in your field of interest. Concentrations & minors are less common, but they do exist. Visit the curriculum links in our listings to learn about your options.
Universities like to play to their strengths. For example, those with a strong School of Business may offer a lot of electives in areas such as Operations Research, Marketing Analytics, and Supply Chain Management. However, if they have an excellent Department of Computer Science, they’ll offer credits in Data Science, AI, NoSQL, and more.
Here are some real-life examples of potential electives:
- Big Data Analytics
- Real Time Analytics
- Advanced Machine Learning & Artificial Intelligence (AI)
- Machine Learning Operations
- Natural Language Processing (NLP)
- NoSQL Databases
- Real Time Intelligent Systems
- Internet of Things (IoT)
- Financial Engineering Systems
- Financial Forecasting
- Portfolio & Risk Analytics
- Logistics Operations
- Supply Chain Operations & Management
- Healthcare Analytics
- Marketing Analytics
- Decision Modeling
- Survey Research Methods
- Design & Analysis of Experiments
Internships & Capstone Projects
A capstone project or internship is one of the most important elements in your master’s degree in data analytics. It’s a chance for you to put theory into practice and impress the heck out of potential employers. Almost every MS in Data Analytics will have one of the following:
- Capstone Project: Under the supervision of a faculty advisor, students are usually grouped into teams of 2-3 and challenged to solve a significant analytics-related problem for an industry partner (e.g. business or organization). Some programs will allow you to choose your own topic. Others may ask you to pick from a list of issues supplied by the partner. You’ll design an analytics research project, apply the appropriate tools & methods, come up with solutions, and present your conclusions through written & oral presentations.
- Industry Internship: You’ll be allowed to work on a real-world analytics project in an outside company or organization. Most internships are scheduled at the end of the master’s degree, in the summer term (e.g. 10 weeks). You may not be collaborating with your fellow students, but you could be working alongside current data analysts & data scientists.
Examples of real-life MS in Data Analytics capstone projects include:
- COPD Readmission & Cost Reduction Assessment
- Real-Time Credit Card Fraud Detection
- NFL Ticket Pricing: Optimizing Revenue Using Variable And Dynamic Pricing Methods
- Visualizing Gentrification in a Large Urban Area
- Time-Series Forecasting of Maple Tree Sap Harvesting
- Regression Model to Predict Earthquakes Using Acoustic Seismic Signal Data
Use the curriculum links in our listings to learn more about what’s available. In certain programs, you may have the option to choose between a capstone and an internship! We’ve also seen programs that contain a mandatory capstone and a voluntary internship.
Master’s in Data Analytics: Admissions
Every master’s degree in data analytics is going to have a unique set of admissions requirements. Some programs are aimed at career changers who don’t have a deep background in computer science. Others are looking for candidates with analytics work experience who want to build on their current skill-sets.
You’ll often see universities using the phrase “holistic approach.” That means they’re looking at every aspect of your application, from your undergraduate transcript & grades, to your résumé, letters of recommendation, and your demonstrated passion for data.
Standard Skill Sets
Generally speaking, many universities will expect you to have:
- A basic background in computing & mathematics
- College-level coursework (or the equivalent) in Linear Algebra, Calculus, Probability & Statistics
- Exposure to common programming languages used in analytics (e.g. R)
- GRE/GMAT scores (sometimes these are optional or waived for certain candidates)
- TOEFL score for international applicants (see the FAQ section on STEM-Designated Degrees)
Some schools may want to see an undergraduate degree in a relevant field (e.g. business, computer science, statistics, hard sciences, economics, etc.). Others will accept any major, as long as you’ve mastered the skills above. Use the admissions links in our listings to read about what’s actually required.
Master’s in Data Analytics: Tuition Cost $
Calculating the Price
An MS in Data Analytics is not going to be cheap. Even a full-time, 1-year program at a state university is still going to put a substantial dent in your pocket. Here are a few items to consider when you’re assessing your options.
- Public vs. Private: If you’re lucky enough to live near a public university with a strong academic reputation in business, computer science & math, in-state tuition prices may be under $20,000. But these schools can be hard to find.
- Tiered Pricing: Be aware that public universities often charge separate tuition prices for in-state students, out-of-state students, and international students.
- Tuition Discounts: Data analytics is a high-demand and well-paid field, so universities are often loathe to offer extra scholarships to master’s students. However, tuition discounts may be available for military students and/or employees of partner organizations.
- Online vs. On-Campus: You may be able to save money by choosing an online master’s degree in data analytics, but you may also be missing out on valuable networking opportunities and in-person career support. It’s a judgement call.
- Corporate Sponsorship: If you’d like to use your degree within your current job, talk to your employer about your plans! Employers are often happy to help defray the costs of tuition if they feel they’re going to see some return. As a data analyst, you’ll be a valued contributor.
Real-World Price Data
Our listings contain links to up-to-date tuition costs for each individual master’s program. We analyzed the numbers and came up with the following ballpark figures for a master’s degree in data analytics:
- Low-End Tuition: $20,000-$25,000
- Mid-Range Tuition: $40,000-$50,000
- High-End Tuition: $60,000+
These may seem like big numbers, but mid-level and senior data analysts earn excellent salaries. Even data analysts on the lower end are still in a position to qualify for competitive wages. If you’re able to work while you pursue a part-time degree, you can also offset your costs.
Which Master’s Degree is Best for Data Analytics Professionals?
Data Analytics: Graduate-Level Specialties
There is no one “right” master’s degree in the world of analytics—you’re at liberty to choose a graduate program that matches your needs & skill levels. Skim through the titles in our detailed listings and you’ll see what we mean! You’ll find degrees in…
- Master’s or MS in Data Analytics
- MS in Data Science & Analytics
- MS in Big Data Analytics
- MS in Data Analytics Engineering
- MS in Statistical Practice
- MS in Social Data Analytics & Research
- MS in Business Analytics
- MS in Healthcare Analytics
- MS in Accounting Analytics
- MS in Economics Data Analytics
- MS in Marketing Analytics
- MS in Civic Analytics
- MS in Data Analytics & Policy
Closely Related Fields
- MS in Data Science with a Data Analytics concentration
- MS in Cybersecurity with a Data Analytics concentration
- MS in Computer Science with a Data Analytics concentration
- MS in Statistics with a Data Analytics concentration
- MBA with a Data Analytics concentration
- MS in Management Information Systems (MIS) with a Data Analytics concentration
- MS in Operations Research with a Data Analytics concentration
MS in Data Analytics vs. MS in Data Science
Data analytics and data science may be related, but they’re very different siblings. Have a look at our glossary of common industry terms to learn more about the two roles.
MS in Data Science
If you’re interested in designing & building new analytics processes, creating software and algorithms, and exploring the possibilities of machine learning, AI & predictive modeling, we recommend you earn a MS in Data Science.
- The Burtch Works Data Science/AI Professionals Salary Report states that most data scientists in their survey hold a master’s degree or PhD. This makes sense, since data scientists have to grapple with the complexities of big data and play a hands-on role in creating technical solutions.
- Data science graduate programs are known to be challenging. Master’s candidates often have an undergraduate degree in a STEM field, solid computer programming skills, and college-level course credits in computer science & statistics.
In large organizations, experienced data scientists may be in charge of a team of data-focused professionals, including data analysts, data engineers, and sometimes even data architects.
MS in Data Analytics
If you’re interested in moving into the world of data analytics from another field (e.g. science, business, etc.), advancing up the pay ladder in your current job, or qualifying for a leadership position in analytics, you should consider an MS in Data Analytics.
- Data analytics graduate programs vary in difficulty. Some are aimed at students who know next-to-nothing about analytics; others are designed for working data analysts who want to advance their skills. Visit the program links in our listings to see if the MS suits your level of expertise.
- You may only need a bachelor’s degree for an entry-level position in data analytics, but companies will often prefer you to have a graduate degree and/or a lot of industry certifications for higher-level leadership positions (e.g. Senior Data Analyst, Chief Data & Information Officer, etc.).
On the fence? You could consider an interdisciplinary Data Analytics & Data Science program that covers both options. Just make sure that it’s offered by a school with a sturdy reputation in computer science & math.
How to Choose the Right Analytics Degree
If you’re having trouble sifting through all of these choices:
- Identify Your Goals: Jot down possible job titles in your fields of interest (e.g. Financial Analyst). Then do a quick search of recent job descriptions to learn what kinds of degrees & majors are preferred at different companies.
- Match the Program to Your Skills: Use the curriculum links in our listings to examine the coursework. Will these classes be too hard or too easy for your experience level? Will you acquire the technical skill sets that employers want to see? Can you work on real-world projects in your area of interest?
- Assess the School: Find out who is offering the program. A master’s degree in data analytics that’s run by the Departments of Mathematics & Computer Science is going to have a different feel/focus than one that’s run by the School of Business and the Department of Operations Research.
- Ask Around: Current students and alumni can tell you what a master’s degree is really like. Hiring managers and mentors can point you toward the best schools and programs. Mid-level data analysts can tell you what’s a waste of time.
We’ve seen master’s programs in data analytics that are hyper-focused on the needs of international corporations and others that are designed to prepare you for a technical PhD pathway. Pick the degree that works for you.
Career Prospects for Master’s in Data Analytics Graduates
What Can You Do with a Master’s in Data Analytics?
You don’t need a master’s degree in data analytics in order to qualify for an entry-level position. A bachelor’s degree in data analytics is the baseline qualification for data analyst openings. Some data analysts will then build on their skills with bootcamps & industry certifications.
However, an MS or Master of Data Analytics could be extremely useful if:
- You have a degree in another field (e.g. math, science, social sciences, psychology, etc.) and you need to prove to employers that you’re able to handle technical responsibilities.
- You want to qualify for a pay raise or leadership opening within your company (e.g. Senior Data Analyst).
- You’d like to branch out into a new realm of expertise (e.g. finance analytics, marketing analytics, healthcare analytics, etc.).
- Your employer is willing to offset the costs of your education.
Keep in mind that some companies & organizations will be happy to hire you, train you up, and then sponsor your graduate studies. But others may be looking for job candidates with a master’s degree who can handle the intricacies of a mid-level position. Talk to companies before you make a decision.
- Technology Sector
- Financial Services
- Government & National Security
Typical Job Titles
- Data Analyst
- Senior Data Analyst
- Analytics Manager
- Data Scientist
- Data Analytics Consultant
- Qualitative/Quantitative Research Analyst
- Chief Data & Information Officer
Aspiring data scientists may want to consider a graduate degree in data science or an interdisciplinary data science/data analytics program rather than a standard master’s in data analytics. They are different fields!
- Operations Research Analyst
- Business Intelligence Analyst
- Business Systems Analyst
- Project Manager
Have a look at our guide to master’s degrees in business analytics if you’re interested in a business-focused career path. You may find a program that’s specifically tailored to your needs.
- IT Systems Analyst
- Technology Risk Consultant
- Financial Analyst
- Market Research Analyst
- Transportation Analyst
Interested in a specific area of expertise? Remember that you can customize your master’s degree in data analytics with relevant electives or a concentration/minor.
- Data Engineer
- Data Architect
If you’d like more info on the roles of data architects & engineers, see our glossary of common industry terms. We also recommend you chat to your industry mentors about these two high-paying career paths. A master’s degree in data analytics may not be the best choice.
Master’s in Data Analytics Job & Salary Data
Data Analyst Employment Data
The U.S. Bureau of Labor Statistics (BLS) groups data analysts in the category of Operations Research Analysts. These are professionals who utilize math and logic to help organizations make informed decisions, collect & analyze data, and develop decision support services. Take a look at the employment & wage maps to see how they’re faring!
- Growth: The job outlook for operations research analysts is projected to rise 23% from 2021-2031 (the average growth rate for all occupations is 5%). So you’re looking at a very healthy employment market.
- Cities & States: As you might expect, the highest employment rates for operations research analysts are in tech-heavy states (e.g. California, Virginia, New York, etc.) and metropolitan areas with a lot of complex data requirements (e.g. Washington DC, Dallas/Fort Worth, NYC, Houston, Atlanta, Boston, Chicago, etc.).
If you’re interested in parlaying your data analytics work into more advanced fields, have a look at the BLS’s report on Data Scientists, the BLS’s employment & wage maps, and the Burtch Works Data Science/AI Professionals Salary Report.
- Growth: The job outlook for data scientists is projected to rise a mind-boggling 36% from 2021-2031. However, the Burtch report also notes that there is an ever-growing number of early career data science & AI professionals entering the industry. So you’re going to have competition amongst your peers.
- Cities & States: Big states like California, New York, and Texas have the highest employment rates for data scientists. However, the highest concentration of jobs may be in Washington DC (think of government work). Burtch also notes that financial services & healthcare industries are increasingly investing in data science & AI hires.
Data Analyst Salary Data
BLS Wages & Salaries
You can use the BLS salary maps to learn more about mean wages for Operations Research Analysts and Data Scientists. Keep in mind that these numbers are an average of professionals from every level of experience (entry, mid-level, and senior positions).
- Cities: Top-paying metropolitan areas for operations research analysts include the San Jose area, the MD/VA/DC corridor, Austin & Houston, and Huntsville—a tech hub in Alabama (e.g. $115,000-$165,000). Data scientists tend to earn the most in areas like San Jose, Silicon Valley, Seattle, and NYC (e.g. $120,000-$160,000).
- States: Tech-heavy states such as California, New York, Virginia, Maryland, Delaware, and Washington often offer the best salaries. But those numbers should be balanced against the cost of living. You may also want to investigate high-paying states that are flying under the radar, including Alabama (Huntsville), Vermont (Burlington), Colorado (Denver/Boulder), and Oregon (Portland).
Mid-Level Data Analyst Salaries
Interested in mid-level roles in data analytics? Have a look at pay data on salary sites. These numbers may be more reflective of your current situation:
- Indeed’s Data Analyst Salaries states that data analysts with 3-5 years of experience can command an average salary of $74,851.
- Payscale’s Average Data Analyst Salary notes analysts with 1-4 years of experience earn an average salary of $62,285. This number increases to $71,129 for 5-9 years of experience.
- In-depth salary statistics are also available for Data Analysts in the U.S. Government; data analysts at Google, Meta, Apple; and analysts at financial firms such as Wells Fargo and JP Morgan Chase & Co.
Considering a shift into data science? The Burtch Works Data Science/AI Professionals Salary Report will give you even more insights into salaries.
- Data scientists with 0-3 years of experience were earning a median salary of $90,000 in 2022. This number increased to $115,000 for professionals with 4-8 years of experience.
- The highest paying sectors tended to be consulting, technology/telecom, retail & CPG (consumer goods), financial services, and healthcare/pharmaceuticals.
- In recent years, data science teams have been offering preemptive retention bonuses, on-the-spot bonuses, and salary increases outside of annual schedules in order to reward talent.
You may be able to request even higher salary offers if you have common industry certifications on your résumé.
Master’s in Data Analytics FAQ
What Should I Look for in a Data Analytics Graduate Program?
We like to call them “quality factors.” When you’re putting together a shortlist of master’s degrees, have this checklist handy…
- Real-World Coursework: The fields of data analytics & data science are morphing by the hour. What is relevant now may be automated tomorrow. Make sure that the curriculum includes a focus on practical technical skills and the flexibility to adapt to new realities.
- Departmental Stature: Learn which department/s are offering the program. What do they specialize in (e.g. operations research, industrial engineering, computer science, mathematics, etc.)? Do they have a great track record in analytics, data science, business, and statistics? Can they offer you access to virtual machines, large-scale infrastructures, and commercial cloud services? Are they receiving research funding for analytics projects?
- Seasoned Faculty: Look at the faculty profiles on the program website and cross-check them on LinkedIn. Are they working as analytics consultants? Are they involved in cutting-edge projects with industries, organizations, or the government? Are they keeping up-to-date with changes in the field?
- Industry Projects: Your program should be arranging internships & capstone projects with top-notch companies and organizations who are interested in supporting (or even hiring) master’s students. For the money you’re paying, you deserve to have an excellent portfolio when you graduate.
- Career Support: The best master’s programs in data analytics will offer all kinds of career opportunities, including funding to attend conferences, discounts on industry certification training, job fairs, and interview connections. They may even arrange seminars & networking events with high-flying data experts from major companies.
You’ll also need to consider prosaic factors like your budget, time commitments, career goals, and skill level. Use the curriculum, admissions requirements & price links to learn if the program matches up to your needs.
What Skills Should I Be Developing in a Master’s Degree in Data Analytics?
If you’re shifting into data analytics from another field, you’ll need to acquire the fundamentals. Data analysts should be:
- Well-versed in analytics approaches (e.g. descriptive, diagnostic, predictive & prescriptive analytics)
- Able to handle a vast number of data sources (e.g. real-time, geospatial, social, etc.)
- Skilled in common data analytics tools, programming languages & software (e.g. SAS, SQL, R, etc.)
- Ready to convey their findings through data visualizations & presentations
The core coursework section contains a list of common skill-sets.
If you’re earning a master’s degree in data analytics in order to build on your foundational knowledge and tackle more advanced technical skill sets, the sky is the limit. You can choose from a huge range of degree specialties, all of which will focus on unique arenas (e.g. big data, financial analytics, marketing analytics, healthcare analytics, operations research, etc.).
Talk to your mentors & employer and check out the section on the MS in Data Analytics vs. MS in Data Science before you decide on a degree. You want to be sure that the skills that you acquire in your studies will actually apply to your job.
Should I Earn a Master’s in Data Analytics or Industry Certifications?
Let’s say you have a bachelor’s degree that includes a solid dose of coursework in college-level statistics and data fundamentals. You’ve completed a few Coursera courses, earned a Google or IBM professional certificate, and you’re assessing career paths. Do you earn a master’s degree in data analytics or pursue industry certifications?
Read current job posts and talk to hiring managers, mentors, and current data analysts before you make a decision. (You’ll often meet these folks at industry conferences.) The answer will depend on your specific situation.
- Price: Master’s degrees are expensive—have a look at our pricing section for ballpark tuition numbers. Be sure of your career goals before you invest in a graduate program.
- Time: A master’s degree usually takes 1 year on a full-time basis or 2-3 years on a part-time basis. Industry certifications often specify that exam-takers have prior professional experience (e.g. 3 years in the workforce).
- Program Practicality: Not all masters’ degrees in data analytics are created equal. Some will help you build an analytics portfolio & prepare you for the Certified Analytics Professional (CAP®) exam. Others will be full of “fluff” coursework and outdated teaching. Do your homework before you commit.
- Internships & Career Connections: Professional certificates & industry certifications are not designed for networking—you earn your credentials and move on. But the right graduate degree can be a gold mine for career-focused students. Strong programs arrange internships, job fairs, interviews, and regular seminars with leaders in the field.
- Leadership Aspirations: You may need a master’s degree in order to qualify for certain senior-level positions. Check with employers to see which major is preferred.
- Peer Competition in Your Area: More & more data analysts are coming out of local universities with undergraduate degrees. So you may have to fight harder to be noticed. A reputable master’s degree will give you an extra edge, but it may also over-qualify you for an entry-level job. Ask around!
Should I Opt for an Online or On-Campus Program?
The answer will depend on where you live & what you want out of the degree.
- Online: Online master’s degrees tend to be convenient, budget-friendly, and built for the working professional. You won’t have to pay for commuting costs & campus fees or squeeze in time to get to your class. You can complete your data analytics internship in your home area and work on group-based projects through virtual meet-ups. But you may miss out on a lot of networking opportunities. See our separate guide to online master’s degree in data analytics, complete with program listings, if you’re thinking about this route.
- On-Campus: On-campus master’s degrees will require more effort & time, but they come with hidden perks. Top-notch schools will give you access to all kinds of cool technical toys & software. You may be able to participate in industry seminars, company site visits, and job fairs. You may have access to resources at the university’s research institute. And you’ll be creating a lot of career connections with your professors and fellow students.
Remember, too, that some universities will offer hybrid programs. That means you can decide to complete some of your coursework online and the rest of it on-campus. This may give you the best of both worlds!
What is a STEM-Designated Degree?
The U.S. Department of Homeland Security (DHS) has created this classification for academic programs. A STEM-designated degree contains at least 50% of coursework in the fields of science, technology, engineering, or math (STEM).
It’s an important classification to know about if you are an international student who would like to work in the U.S. after graduation.
- Most international students in full-time master’s degree programs apply for the F-1 Visa. Students with a F-1 Visa are usually eligible for 12 months/1 year of Optional Practical Training (OPT)/temporary employment after graduation.
- However, if you are enrolled in a STEM-designated educational program, you are eligible for an extension of up to 24 months/2 years of Optional Practical Training (OPT) on top of the initial 1-year OPT agreement (36 months in total). OPT can also put you on the path to a work visa.
Check with the program coordinator to learn if a full-time master’s degree in data analytics is a STEM-designated program. They almost always will be!
Is a Master’s in Data Analytics Worth It?
- Not Worth It: Some master’s programs in data analytics are simply not worth your time—they’re condescending in their approach, full of outdated technical coursework, and completely divorced from the real world.
- Worth It: However, there are plenty of master’s degrees that are great value for money. They’re designed to help you advance step-by-step through the field. They’re packed with internships & career opportunities. And they’re taught by analytics professors who consult for big companies.
If you’d like to shift careers, climb the data analyst job ladder, and/or be exposed to new discoveries in the field, then a graduate degree is a feasible option. But before you invest in an analytics program, ask yourself the following questions:
- Which analytics skills do you really need before you can move up in your field?
- Are employers actually requesting a master’s degree in job postings?
- Will you get a salary boost or promotion for your efforts?
- Is there something you can gain from a master’s degree that you can’t get from a bootcamp, certificate, or industry certification?
The right degree can open countless career doors. The wrong one can drain your bank account & your enthusiasm. Never settle for second-best!