WGU “Master of Science in Data Analytics” (MSDA) Review

15 min readMar 26, 2021

Introduction

In December of 2019, I began reshaping the back-half of my career by enrolling in WGU’s Master of Science in Data Analytics (MSDA) online degree. The timing was incredibly lucky because the pandemic started shortly after I was admitted, enabling me to focus all that extra stay-at-home time into the degree.
Ten-plus months and 1,208 “after-work” hours later, I was the happy recipient of an MSDA degree. With perspective four months later, I am still just as happy about the whole process and the outcome. My only regret is not recognizing this option was available to me years earlier.

Overview: WGU’s MSDA is 100% online enabling you to better juggle a full-time job, family commitments and other life obligations. The learning model is competency-based allowing you to learn at your own pace — be it fast or slow. Whether you pass final exams and final projects depends on whether you understood the material. If you understood, you pass. If not, you fail and receive a few structured retries before washing out. For an introverted self-starter with some existing knowledge like me, the process was bliss. Courses where I had existing expertise went fast. Courses where I did not and had steep learning curves were still manageable because I could deeply focus on each, one at a time, through to completion. I enjoyed working thru the lectures, the reading material, the quizzes, the final projects, and even preparing for the final exams each night. The structured learning was energizing each evening as I could always make forward linear progress with each hour of effort put in — check off another chapter of reading, or another video lecture series, or another practice exam, etc.

What is “Data Analytics”?

Short Answer: it is roughly synonymous with “Data Science”. It is the intersection of IT / Computer Science with Math/Statistics with Domain / Business Knowledge.

Long Answer: “Data Analytics” is micro-focused on extracting meaningful insights to make actionable changes, mostly using structured data. “Data Science” is macro-focused and tries to predict the future and discover new questions to drive innovation, often using unstructured data. Both involve data mining, mapping, munging, AI, machine learning, modeling, using modern analytic and programming tools like Python, R, SAS, SQL, using visualization tools like Tableau and XL, etc. Mastering “Data Analytics” will set you up for a career as a data scientist, research analyst, data engineer, advanced analytics expert, data analyst, business intelligence analyst, or business analyst.

Side Note: The correlation between Data Analytics vs. Data Science on Google trends is interesting — take a look.

Is the Degree Any Good?

Yes, the degree is considered good. It consistently ranks in Top 10/ 20 lists of best online master’s degrees in data science: here, here, here, here, here, and here. It is accredited by NWCCU, the same organization that accredits giants like the University of Washington, Brigham Young University, etc.

Leveling Up? If you already have many years of experience as a “Data Analyst” or “Data Engineer” or “Programmer Analyst” and you just want to transition into a “Data Scientist”, then completing this degree can be a good approach. However, if you are young and recently finished a bachelor’s degree, then maybe a traditional brick and mortar graduate degree would provide better results (especially given the cohort groups and networking opportunities which will drive your subsequent job search — online programs cannot compete).

Graduation Rate: The 3-year graduation rate ranges between 63% to 71%, translating to a washout rate of 29% to 37%. Thus this is not a “diploma mill” and students do wash out (WGU Annual Report, page 24).

Opinion Poll: The WGU MSDA “Career Outlook” site sums up the answer nicely in the two charts below, taken directly from the WGU website. Harris Poll survey results clearly show that both employers (of WGU grads) and employees (WGU grads) are happy with the degrees.

Anecdotally, the degree has checked some boxes for me that opened doors for a career transition. Looking back, I am happy that I put the time and effort in to completing the degree.
▪ As a Prospect, I was really excited upon first learning there was a viable path for me to attain a graduate degree, and it as all online! I was fired up and could not wait to dive in.
▪ As a Student, I thoroughly enjoyed taking the classes, learning the material, practicing the material in projects, and reinforcing it during final exams prep.
▪ As a Graduate, I fondly look back and am so happy with the decision to put in the effort to obtain the degree and advance my career.

Use Degree for Career Goals: A related suggestion is to discuss obtaining an MSDA with your boss as part of your annual career goals. Some firms might either pay part if not all the costs. Other firms might give you some comp time. Expect most firms (especially smaller ones) to do neither for practical reasons.
Regardless, linking your outside career plans to your annual company career goals is a good idea. It shows you put in the effort to grow and improve. It shows where you want to go (good managers want you to succeed and will find opportunities for you to grow into). If nothing else, it is one less item you have to come up with on the annual performance review.

Is the Degree a Good Value?

The final cost depends on how fast you can work through the classes. The degree currently costs $3,835 per 6-month term. You can take the classes as fast or slow as you want, but the price remains fixed at $3,835 per term. That means if you could complete all 11 courses in 6 months, you would pay $3,835 — but that is a highly unrealistic time frame.

“Scholarships”: I received literally dozens of emails about “scholarships” that would cut many thousands of dollars off my tuition; but did not participate, so cannot comment. Please do be aware these scholarships exist and may pay most of your first quarter — I am not sure they continue after that, so might be one time to hook you.

Ranking Organizations: the WGU MSDA degree has been named a “Best Value School” by University Research and Review for seven consecutive years. The degree routinely makes the top 10 / top 20 lists of most affordable data science Masters degrees, here, here, here, here, here, and here.

Will the Degree Get You a Job?

By itself, probably not. Sure, if this were an Ivy League Masters of Data Science and you’d paid six figures for it, then it would likely land you a job at a corporate giant upon graduation with no prior experience. However, with a WGU degree, you are buying competency and experience, not networking and name brand reputation.
For context, if an entry level Data Scientist with just two years under his/her belt has accumulated 4,160 hours of experience as a baseline, then the 1,208 hours I spent completing the MSDA degree is 3.5x smaller! Bottom line is that actual work experience matters.

What the degree does do is propel you far down the path towards getting a job — just not all the way. It proves to an employer that you can focus and achieve goals, that you can follow a plan and carry out tasks, and that you have a foundation of basic understanding in place. If necessary, having the MSDA on your resume or LinkedIn can serve as a tiebreaker between the final few candidates. These are just some of the advantages that “armoring up” with the MSDA degree can provide in your job search.

Learn from My Mistakes: If you plan properly, you can roll your coursework (e.g.: final projects) into your career portfolio to share with prospective employers — wish I’d done that. WGU also offers Career & Professional Development services, career advisors, weekly webinars & events, and Job Fairs. Unfortunately, I did not take advantage of these so I cannot comment.

What are the Courses?

The table below istaken from the WGU MSDA program guide and shows the standard path in which courses should be taken. However, ultimately you and your course counselor decide what course order is best for you. The default is 4 terms (2 years), although many people can do it faster in 3 or even 2 terms if they work hard. There are 11 courses totaling 31 competency units (CUs) to complete the degree.

The courses are grouped by five areas of study: Data Analytics, Data Management, Data Mining, Data Visualization and the Capstone.

It is beyond the scope of this article to get into the details behind each course, but here is the 10 page Program Guidebook PDF for you to review if you want to better understand what each course entails.

How Much Effort is Required?

It depends. Quite a bit if your goal is to learn and grow and really understand the material. Less if your goal is to merely pass and get the degree as fast as possible.

Difficulty: Although most final exams are multiple choice (one exception involved roughly 50% writing SAS code); they are not easy, and to pass you must spend ample time studying. Final projects were also difficult, generally taking me half to two-thirds of the overall course time. If you have years of work experience for the given course, then you can complete the work 2x or 3x faster than the average person (I did so with the SQL class at about 4x). However, when the material is new to you, plan on putting in a lot of effort to complete the course.

Study Plan as Checklist: From the outset, I front loaded each course by setting up a detailed Study Plan of all available learning materials and tasks. I then used it as a checklist to track progress through to completion, one course at a time. Above and to the left is a sample excerpt from one of my Study Plan / checklists for the “C741 Statistics for Data Analytics” course. Sure, part of its value was in organizing the workload, but it also gave me self-motivation. Through accidental “gamification”, I received mental reward by scoring “points” as I checked off lines of study in my plan. Example: “I can check that line item off if I just power through for 45 more minutes tonight”.

Making incremental progress, no matter how small, is fun and self-reinforcing so long as a measurable “score” exists to play towards.

By the Numbers: My experience is depicted “by the numbers” in the bullet points and table below.

Caveat #1: The course curriculum changed since I completed the degree 5 months ago, so classes I took below no longer completely align with classes currently offered.

Caveat #2: regarding paper size, page length, lines of code, or capstone project video length — there is no limit, just cover everything required in the rubric as succinctly as possible and you will pass on the first try. It is actually a bad thing to go “off-rubric” and try to add unnecessary size or complexity (make it easy for the graders, even map out the sections in your work to the corresponding rubric line items).

Reddit Bias: On a quick side note…if you google Reddit WGU MSDA posts, you will see a lot of discussion around “finishing the program in one term” (6 months) or “finishing the first 3 classes in 3 weeks”. Do not mistakenly draw the conclusion that the program is easy, or that it is a diploma mill. Even for me, some of the classes did only take one week and 32 or 36 hours to complete, but those were the simpler, 1 and 2 CU classes that tend to be scheduled in the front half of the degree…and for which I had literally hundreds of hours of prior experience across 25 years in the industry. Those Reddit threads frequently do not follow through later with the fact that courses in the back-half tend to be more difficult and thus take longer. WGU is smart, they put the easier introductory classes up front to get you started, build a solid base, and establish your habit of making steady progress. The course mentors even work with the student to re-arrange course order. By the time you hit the more difficult classes, you have “comfortably completed” much of the degree and are “invested” and thus less likely to just give up and wash out. That approach benefits student, instructor, and university; so just be aware of “the rest of the story” when reading those Reddit threads.

How Much Prior Experience is Required?

It depends. In general, the more IT and math experience you have, the faster you will grasp the concepts and get thru the course material, the exams, and the projects. The less experience you have, the more you will need to study to compensate. Less experience = more effort = longer course completion time = higher cost…but still achievable.

Broad Experience: Speaking from my own experience, if you already have (a) programming, (b) data, and (c) math or statistics experience from an I.T. career and STEM classes in high school or college, then you will do fine and enjoy building upon that existing knowledge.

Some Experience: Students with strong mathematics background, but little to no programming or database experience posted that they do fine in the program. Conversely, students with heavy programming and/or database experience but no statistics background also tend to do fine according to posts (sources: Reddit and internal WGU course chatter). The common thread is that students on both these paths hit the ground running with a solid foundation in 1/3 to 1/2 of the core material.

How are Courses Graded?

Competency: WGU is competency-based, a “method of academic instruction and evaluation based upon students demonstrating their mastery of a subject” (Rasmussen.edu). Students demonstrate mastery of competencies at the end of each course by completing and passing either an “Objective Assessment” (final exam) or a “Performance Assessment” (final project). Course flow tends to alternate back and forth between the two equally.

Grades: There are two course “grades”:
▪ Fail (traditional F, D, C) and
▪ Pass (traditional B).
▪ Excellence - I would argue there is a third and rarer grade of Excellence Award (traditional A+). I only received three of those out of eleven courses, in spite of trying hard — so these are not just handed out like candy on Halloween where everybody gets some.

Proctored Exams: Also note that *all* final exams (“Objective Assessments”) are proctored. This means they are scheduled to start at a specific time at least one day in advance, but often a week or two in advance. You must be sitting in a room in your home in total silence with the door locked so that no disruptions occur. You must have an approved video camera for the proctor to watch your every move and ensure no sounds are made. You must provide proof of your identity (driver’s license) at the start of the test. You must have your ears and head uncovered, and you cannot have a cell phone within 6 feet. The rules are strict to avoid cheating.
Any violation of the rules will result in the test being immediately terminated. Depending on circumstances, you will either fail that test, or receive a waiver that does not count against you if it was a provable internet or similar technical problem. For either outcome, you must retake a new test with new questions.

What Kind of Interaction Can I Expect?

It depends. From the moment you show interest, WGU assigns an enrollment counselor to determine if the program is a fit, to help you work through the enrollment process, get all your necessary paperwork turned in, etc.
From there, you are handed over to a program mentor who works with you throughout the remainder of the degree. The mentor discusses and coordinates your degree plan with you, activating them for you register, emailing you kick-off learning materials, tip sheets, suggested YouTube pre-trainings, etc. The mentor talks with you at least once a week to check in on progress, help remove any barriers, resolve any issues, etc. You interact with your mentor the most of any WGU staff. They are very helpful.
The course instructors (professors) have office hours in which you can do online meetings or phone calls to ask questions, etc. The three interactions I had with the professors were all excellent and resolved the confusion on my end quickly. Note that I am an introvert and a self-starter, so I tend to avoid interaction until I really need it — and that model works fine too because so much targeted information is pushed to you in the form of FAQs, tip sheets from former students, suggested reading lists, etc.
There are also program faculty who oversee course content, but I am not sure what reasons you’d have or how you’d go about contacting them (other than to make course content suggestions via email which is readily available).

Cohorts: One gap is around the notion of cohorts, or a peer group of individuals taking the same classes at the same time. Traditional brick and mortar universities, especially MBA programs, have strong cohort groups with many team projects for you to sharpen teamwork skills and build a life-long network. That will not happen at WGU. WGU tries to cover the gap with various IM groups, a career placement center, networking events and heavy email promotions…but full disclosure, I cannot comment on them because I did not participate in them (😊). For me it was not a priority because “half-ish” of MSDA work tends to be more solitary, plus I already had the networking and team building boxes checked from 25+ years of work experience. If you just have a bachelor’s degree with little work experience, then perhaps you should consider the cohort groups and networking opportunities of being physically present in a traditional brick-and-mortar university might be a better path than this online degree.

What are the Admission Requirements?

To apply for the degree, you must submit official records of completion with a minimum GPA for either:
a) An existing Bachelor’s degree in Science/Technology/Math/Business, or
b) Any Bachelor’s degree PLUS relevant IT certifications / experience / coursework
c) If applicable, your resume emphasizing technical / data / programming skills

No GRE or similar graduate entrance exam is required.

Covid Impact on GREs: during the pandemic, many schools have temporarily waived GRE’s, SAT’s, and ACT’s. However, some schools opted for students to still do proctored at home versions.

Conclusion

I highly recommend the WGU Master of Science in Data Analytics if you are looking for a graduate degree in data science to further your career. Although by no means “easy”, if you put in the hours and the effort it can be one of the fastest, most flexible, and most affordable paths to a “data science” graduate degree.

If these insights and opinions were helpful, please hit me up on LinkedIn or subscribe to my YouTube channel DataResearchLabs where I drop related training content and tools. A matching slide deck (cc) for this article is located out on GitHub with additional content.

Addendum #1 — Related Online Masters

If you either have an MSDA and want to augment, or perhaps are more interested in an MBA or graduate degree in computer science or cyber security. If so, here are some similar degrees to checkout:

[01] University of Texas at Austin, EdX, MS in Computer Science
[02] WGU, MS in Cybersecurity
[03] Purdue, MS in Cybersecurity Mgmt
[04] Georgia Institute Technology, EdX, MS in Data Analytics
[05] University of Texas at Austin, EdX, MS in Data Science
[06] Purdue, Master of Health Informatics
[07] Purdue, MBA
[08] WGU, MBA
[09] WGU, MBA in Healthcare Mgmt
[10] WGU, MBA in Information Technology
[11] WGU, MS in Information Technology Management
[12] Purdue, MS in Information Technology Management

Addendum #2 — Level Up to Online PhD?

If you want to level up and go beyond a master’s degree all online, there are two paths. One is to pursue a PhD for teaching and research by contributing new knowledge. Two is an applied Doctorate for corporate professionals to research practical applications of existing knowledge and theory. If either path appeals, then look through these related degrees: