How to Become a Data Analyst (Without Going Back to College)
Supply and demand… we all know that as job seekers, high demand and low supply work in our favor. It's a booming job market already, but even more so for data analysts.
The 2018 KMPG CIO Survey found that 46% of Chief Information Officers see "big data and analytics" as the area most in need of additional talent to support growth.
While this impacts careers in data science and data analysis alike, this article focuses strictly on a career as a data analyst, as it's a bit easier to pursue without an advanced knowledge of (read PhD in) Statistics.
Alright, now let's dive in - how can you become a data analyst?
What does a data analyst do?
In simple terms, a data analyst takes data that's been gathered and uses it to help their company or companies make informed business decisions. A data analyst gathers data on specific topics or metrics, often called Key Performance Indicators (KPIs), analyzes that data, and then prepares and presents their findings.
They also work with business development and product teams to use past data in order to set KPIs and track performance over time.
How can you become a data analyst?
Now that you know what a data analyst does, how do you develop the skills necessary to become a data analyst?
First off, let's take a look at what you need to know from a technical perspective.
- Statistical modeling
- Experience using statistical packages to analyze datasets (Excel, SPSS, SAS, R)
- Knowledge of and experience with reporting packages, databases, and programming
- Strong analytical skills and the ability to organize, understand, and identify trends in data
- The ability to share findings with others
- Data visualization skills and familiarity with programs like Tableau
Lots of sources will tell you you need a degree in a related field to get hired, but with large companies like Google and Apple ditching their degree requirements, what you really need is demonstrated experience in the field.
Consider Coursera's statistics courses and remember that regardless of your major, if you took any stats courses in college, they're great things to flag on your resume when applying to data analyst roles.
Any quantitative academic research (be it in sociology, psychology, or chemistry) will also be highly transferable, so be sure that's listed as well. (You don't need to have studied economics to understand modeling, but recruiters don't always know that, so do what you can to make it obvious to them!)
Lots of the tools you'll need to use as a business analyst offer free tutorials and certifications, so be sure to check them out as well:
Once you've got the basics down, look at job descriptions for data analysts at some companies where you'd like to work. Read each item on the list and ask yourself if you've done any work to prove that you're capable of the listed task. If you have, jot down what you've done and why it's relevant.
If you haven't, think of projects you could do independently to demonstrate that experience. Consider applying for internships, asking your current employer to allow you to take on data analyst tasks (companies love actionable data, so this should be an easy pitch), or working on a passion project with friends who already have experience in the field.
Within a year or two, you'll easily have enough experience to score an entry-level data analyst role, or maybe even pivot into (or create) one at your current company.
So, recap - how can you become a data analyst... as quickly as possible?
- Understand what the role entails
- Explore free resources to gain exposure
- Review the list of required technical skills
- Identify gaps in your existing skill set
- Take tailored cost-effective and free courses to address the gaps (be sure to make use of free software-specific trainings)
- Start looking at job postings at your target companies - what skills are you still missing?
- Design projects (at your company, with friends, or independently) to give yourself the opportunity to demonstrate your knowledge in those areas
- Get an internship, if feasible/necessary
- Apply to full-time roles! (And don't forget, if you work at a small company that doesn't yet have any data analysts, you can always pitch the role to them!)
Remember, you can always go back to school for an advanced degree to unlock even more earning potential later on, but why put two years of time and money into a degree when you could dive straight into the career first?
When Danielle Satterfield attended a PowerToFly networking event with cloud-based observability platform New Relic last December, she wasn't actively looking for a job.
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