How to Get Educated About Analytics

Looking to get started in analytics or data science? Are you better off pursuing a degree or getting a certificate? Here's a closer look at the different paths available to aspiring data professionals.

Lisa Morgan, Freelance Writer

September 26, 2017

5 Min Read
<p>(Image: Gundam Ai/Shutterstock)</p>

Analytics education is anything but static. It's so hot now that lots of education-focused organizations are offering traditional degree programs, online degree programs, certifications and courses.

As we well know, analytics capabilities and best practices are evolving, as is the application of analytics to business problems. In addition, there's still a shortage of data-savvy people. All of that is creating demand for analytics-oriented education which is and has paved the way for so many new offerings. The question is, which option is best for you?

There are a number of ways to answer that question, some of which are more productive than others.

If you go online, you may find yourself overwhelmed by the choices. If you contact someone from any one of those organizations and ask their advice, they'll probably tell you their program is the best.

In my view, there is no one best option. The answer depends on several factors which include the amount of time you have to dedicate to the program, the focus of the program and the cost (assuming your employer won't cover the cost).

Probably the most frustrating approach is to look at the growing haystack using a Google search and start clicking on the endless stream of links. If you do that, you'll probably be more confused than when you started your search. Lists of "top schools" may help narrow the focus as may a few suggestions below.

Degree or Certificate?

Data analytics degree programs didn't exist until recently. So, if you lack an analytics degree, you're in good company. Many universities offer formal BA/BS and/or MA/MS programs now, and they may have online degrees or certifications as well. For example, the W.P. Carey School of Business at Arizona State University offers MA and BA degrees in Analytics which can be earned online or as a full-time student. MIT Sloane School of Management offers a one-year Master's degree program, an undergraduate degree, and a certification program, albeit for graduate students. However, MITx (an online MIT entity) has an online data science certificate program, which I can vouch for personally.

Degrees and certificates don't carry the same weight, especially if you lack prior relevant work experience. A degree represents a level of mastery and years of dedication. However, employers are also well-aware that analytics degrees are new. Even if the degrees weren't new, deep experience and a certificate or no certificate might be more valuable, depending on the candidate and position. A certificate also suggests a level of mastery, albeit the kind that can be earned in weeks or months versus years. If you have a some kind of degree, such as a business or information systems degree, analytics-related certification tends to indicate a dedication to continuous learning, which is a good thing.

There are a few other points to consider such as the school's pedigree, how long they've had programs, what students and former students think of them, the companies that work with them, and the companies that hire from them. If you're using education as a means to a promotion, find out what matters most to your employer.

Also realize that two programs with the same title can differ greatly in terms or course material, focus, faculty competency and how well faculty members communicate. Some professors or instructors are very articulate and easy to understand, even when they're presenting highly technical material. Some are not.

In addition, understand your limitations because certification courses tend not to list prerequisites, like degree programs. For example, (and not surprisingly), a course may require students to use Microsoft Excel Professional Edition at a minimum. That's may not a problem if you have access to the program at work, but if you don't already have the software, be prepared to invest more than you anticipated in your certification. Similarly, some courses require a deeper background in math than others.


Online courses tend to emphasize that the coursework can be accomplished on a "flexible" schedule but you may be required to repeat the course in a particular time frame to earn the certificate. You may think that's not a problem because you're psyched! Then life happens. If you suspend your study of such a program, you may be required to start from the beginning when the next class begins.

Part of the reason some self-study programs work within a given time frame is that it gives the "class" the ability to interact with the faculty and other students. EdX has many such programs, some from top universities, including MIT.

One of the cool things about EdX is you can take courses for free and only pay if you want the certificate associated with the class. The class may still start and stop at particular dates, but hey, the classes are free so you can get the syllabus, go through a module or two and see whether the course is suited to you. Right now, EdX has 122 online courses available that focus on analytics. Some of them are broad, such as the ColumbiaX Statistical Thinking for Data Science and Analytics. Others are narrow including the UC BerkeleyX course in Marketing Analytics.

It's Your Choice

If you ask 10 people about which degree, certificate or course you should pursue, you'll probably get 10 different answers. Ultimately, your path should align with your interests and career goals.

That said, if your choice requires a heavy investment in time, money or both, don't make the decision in a vacuum. Consider some of the points above, talk to people and do some research so you have a better idea of what's really right for you.

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About the Author(s)

Lisa Morgan

Freelance Writer

Lisa Morgan is a freelance writer who covers business and IT strategy and emerging technology for InformationWeek. She has contributed articles, reports, and other types of content to various publications and sites ranging from SD Times to the Economist Intelligent Unit. Frequent areas of coverage include big data, mobility, enterprise software, the cloud, software development, and emerging cultural issues affecting the C-suite.

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