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Data is the new frontier of the 21st century, ripe for exploration. Data science—obtaining, analyzing, and reporting on data insights ranging from business metrics to user behavior—is an ultra-buzzy field right now. So you might have found your interest piqued if you’re into statistics, languages like Python and SQL, and data-driven problem-solving.
You’ll be happy to know that all the buzz around data science isn’t a bunch of empty hype. Data analyst jobs are extremely abundant, lucrative, and intellectually fulfilling. (Some companies treat the titles of “data scientist” and “data analyst” as synonymous. For the purposes of this article, anything not specifically identified as pertaining to data scientists will refer to data analysts. There’s more to come on the distinction between the two.)
Companies are buckling under a deluge of information newly available to them in an incredibly rich variety. Petabytes of data offer detailed intelligence on everything from when, how often, and where customers are using products, to precisely how a process is functioning along a near-infinite quantity of touchpoints. But all that data is useless to a business without someone to organize it, evaluate it, glean actionable insights from it, and communicate those insights visually, verbally, or both.
As Harvard Professor Gary King told Harvard Magazine, “There is a big data revolution. The big data revolution is that now we can do something with the data.”
That’s where you come in.
High Demand for the Highly Skilled
Data analysts are in extremely high demand, but the work itself is equally demanding. Data science sits at the intersection of statistics, business intelligence, sociology, computer science, and communication. You’ve got to be a numbers whiz, but also a strong communicator; you’ve got to be an analytical mastermind who can also think abstractly.
There’s an incredible potential, already being fulfilled in industries as varied as medicine and manufacturing, to capitalize on the deep data pool available to change the course of how products are made and marketed, how processes are executed and optimized, and how society at large advances. No pressure or anything.
To situate yourself for success as a data analyst, you should be familiar with five core competencies: programming, statistics, machine learning, data munging, and data visualization.
“You obviously need the technical skills to be able to extract data and run statistical analyses, but there is the more intangible ability of finding patterns or irregularities to report on,” said Erik Berger, a Senior Web Technology Manager who’s been working in data analysis for 11 years. “To be good at it, you need to fully understand the nature of the business that you’re analyzing—just looking at the numbers is only half the story.”
If you’ve got what it takes, there are plenty of companies eager to take what you’ve got. The McKinsey Global Institute has predicted that by 2018 the U.S. could face a shortage of between 140,000 to 190,000 people with deep analytical skills, and a shortage of 1.5 million managers and analysts who know how to leverage data analysis to make effective decisions.
It’s not just the skills needed, it’s also the raw manpower. In a survey by Robert Half Technology of 1,400 U.S.-based CIOs, 53% of the respondents whose companies are actively gathering data said they lacked sufficient staff to access that data and extract insights from it. Translation: you are sorely needed.
What Data Analysts Make
Since the field of data science is still nascent, the Bureau of Labor Statistics doesn’t have any, well, data on data analyst salaries. But according to GlassDoor, the national average salary for data analysts tops more than $60,000.
As the need for data pros amplifies, so does the interconnecting web of data jobs. Data analysts often work closely with data scientists (again, note that you’ll find some organizations conflate the two titles), database administrators, data engineers—and probably additional roles as the industry continues to develop.
Here’s some financial context for your prospects as a data analyst, according to DataJobs. National salary ranges for the following data jobs:
- Data analyst (entry level): $50,000-$75,000
- Data analyst (experienced): $65,000-$110,000
- Data scientist: $85,000-$170,000
- Database administrator (entry level): $50,000-$70,000
- Database administrator (experienced): $70,000-$120,000
- Data engineer (junior/generalist): $70,000-$115,000
- Data engineer (domain expert): $100,000-$165,000
Each of these roles contributes critically to obtaining, analyzing, and delivering data. Embarking on a career as a data analyst gives you plenty of options down the road as you hone your skills.
It’s important to note that, given the talent crunch and the dynamic state of the data industry, compensation is far from standardized. Right now, salaries are essentially as much as a company is willing to spend to fill their immediate needs.
The bottom line? Your bottom line as a data analyst will be in great shape.
Where the Jobs Are
It’s no surprise that data jobs are seriously skewed toward the main tech hubs of the country: San Francisco and New York.
While SF represents just 7% of the jobs posted on Dice, it’s home to 24% of the Big Data jobs posted. New York and the nearby Washington, D.C./Baltimore area have the second and third most Big Data job postings.
That said, prime data analyst jobs are available in plenty of other metropolitan areas around the country. Boston and Seattle each claim just 3% of the jobs posted on Dice, but are home to 7% and 6%, respectively, of the data gigs posted, which means they markedly over-index on exactly the roles you’ll be looking for. Same goes for Philadelphia and L.A.
This heat map from Payscale displays the geographical spread of of data analyst jobs:
As you can see, you’ve got plenty of options when it comes to job location. There’s more good news: if your desired hometown isn’t brimming with data analyst jobs, know that there are more opportunities for contract, freelance, and remote work than ever before. You’ve got the freedom to determine what works best for your goals, lifestyle, and experience.
The Bottom Line
Whether you’re contemplating a career change or just setting off in the professional world, pursuing the path of the data analyst holds serious promise for both your bank account and your brain.