Data analytics is useful in nearly every enterprise, from farming techniques to online fashion retail. Wherever large sets of numerical information accrue, a data analyst can figure out how to mine them for useful insights.
Data analytics consultants use data sets and models “to draw meaningful insights and solve problems,” according to the Northeastern University graduate programs blog. As a data analytics consultant, you might work in:
With a little experience, education, and know-how, you can earn one of the 2.3 million jobs that seek candidates skilled in analytics. You might be required to put in long hours and solve complex problems, but the compensation should make the effort worthwhile: the average salary for analytics consultants is $96,616, which is about $40,000 higher than the average for all workers.
Wondering what else you need to know about becoming a data analytics consultant? In this article on what does a data analytics consultant do, we discuss:
The requirements may vary based on individual jobs, but being a data analytics consultant generally means immersing yourself in numbers and then translating your findings for the people who need to use them. To put this in geekier terms: if data analytics is The Matrix, you are Laurence Fishburne, and you need to bring your colleagues (Keanu Reeves) in. Note that data science—though a closely related profession—is different. Where data analysts focus primarily on data sets and tangible guidance, data scientists focus more on creating models and speculative projections.
There are so many skills a data analyst can have that you’re probably not going to have every one, especially starting out. Keep in mind that certain skills will get you further than others.
Top skills that every data analyst consultant should have include:
The good news is your expertise transfers from one field to another. While analysts sometimes specialize in a specific field, you don’t have to. If you know how to work numbers really well, it won’t matter if you are crunching them for a large trading firm or an NBA basketball team.
That said, it can be beneficial to find a niche and become an expert. According to 5 Tips for Wharton MBAs Interested in a Career in Data & Analytics, specialization provides not only a “solid understanding of the core principles” of your industry of choice but also a familiarity with “the atmosphere, work/life balance, and recruiting norms” of that industry.
Depending on the way your career advances, it might be useful to acquire familiarity with other skills and programs, including:
Data science professionals can use their knowledge and skills in many ways and in almost every industry. You might specialize in business intelligence or robotics or healthcare informatics. There are almost too many options.
90 percent of data scientists hold master’s degrees, and 47 percent hold doctoral degrees. ( )
The Bureau of Labor Statistics sets median data scientist annual pay at just over $100,000. Top-paying sectors include ( ):
- Computer and peripheral equipment manufacturing ($148,290)
- Semiconductor and other electronic equipment manufacturing ($142,150)
- Specialized information services ($139,600)
- Data processing, hosting, and related services ($126,160)
- Accounting, tax preparation, bookkeeping, payroll services ($124,440)
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Most data analytics consultants pursue undergraduate study “in mathematics and statistics, or they supplement a non-quantitative background by learning the tools needed to make decisions with numbers,” according to Northeastern University.
Nearly all STEM degrees are useful for aspiring data analysts. Common options include:
Hands-on experience is often more important than the classes you take, however. “In academia, data is clean, and takeaways are apparent,” says Greg Caiola, in his article for Wharton. “In the real world, data is messy and takeaways are opaque. The real skill is learning how to thrive in that complicated environment.”
Caiola recommends finding a problem that you care about and solving it with data–he uses the example of fantasy football drafts. Internships can also be quite helpful in establishing a career in data. To find one, use resources like:
You might even approach a local business to set up a partnership. There are many ways to gain experience with data analytics. Most of them happen outside of the classroom.
Though certainly not necessary for working in the field, a data analytics certification or two might help advance your career. Some of the best certifications for data analysts are:
You might also opt to earn a certificate from a college or university. The Harvard University Extension program offers a Data Analytics Certificate to applicants who have a basic understanding of R. The program takes a year-and-a-half to complete and costs around $11,000.
Too expensive? The Massachusetts Institute of Technology open courseware program is free. The program is geared toward motivated self-starters (two words that often appear on a job description) who want to start learning data analytics right now.
When it comes time to look for work, demonstrated experience will most impress employers; certifications are one way to show you’ve \put in your hours and have the necessary chops. With proven work experience and an impressive track record, many employers will want to hire you, with or without certifications).
Again, the answer to this question depends on what you want out of your career as well as other personal and professional circumstances. Spending between a year and five years in a master’s program (depending on the school and whether you are full- or part-time) and potentially more than $100,000 might not make sense, especially if you have a family and full-time job. Even with flexible online programs, you still need to put in the work, which can be daunting.
Still, if you are looking to move your career into upper-level management, a graduate degree could be helpful. In some cases, your employer might be willing to help cover part (or even all) of the cost of a graduate degree.
If you do decide to earn a master’s degree, you will need to choose between a Master of Science (MS) and a Master of Business Administration (MBA). The main difference between these programs is an MS digs deeper into programming, software applications, and advanced mathematics, while an MBA is a broader, more management-focused program. An MS generally takes less time to complete.
The degree you choose depends entirely on your situation, but some examples of analytics degrees from esteemed institutions include:
There is quite a bit of mobility in the data industry, especially for those who possess a graduate degree. Some other sectors that those with an MBA or MS in data are qualified to work in include:
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