Every day, the world generates 1.145 trillion megabytes of data. There’s a wealth of information floating out there, and various industries need to make sense of it.
For this reason, the demand for data analysts has shot up, and you can bet that it won’t die down anytime soon. So if you’re considering switching careers, data analysis can be a decent field to go into.
However, you can’t just jump straight into a data analyst job. Here are the steps you need to take to get there.
Most entry-level data analysis jobs will require you to have at least a bachelor’s degree. While it’s possible to get careers in data science without one, it’s best to invest time in your education. That way, you’ll stand out against applicants who don’t have a college degree.
But not everyone has the time or money to invest in a college education. It might be a bit easier if you’ve already got a relevant degree though. Online courses can also be a godsend since they’re cheaper, and you can learn at your own pace, without dropping your current job and other responsibilities.
Fortunately, times are changing, and employers are starting to look past bachelor’s degrees. They value experience and skills just as much, if not more, so learning a programming language, statistics, data visualization, cleaning, and preparation, as well as building up your portfolio, can supplement a lack of formal education.
If you choose to enroll at a university, then they’ll teach you the relevant data analysis skills you’ll need for your career. Otherwise, you’ll have to DIY some lessons.
Basic data analytics involves statistics; either brush up with old textbooks or find lessons and tutorials online if you’re not pursuing your bachelor’s. You should study data analysis in spreadsheets too, as well as in other tools, like Power BI.
Also, you’ll need to choose a programming language to specialize in. Data analysts will need to know Structured Query Language (SQL), so be sure to master this one, as it’s used for querying and manipulating databases. Besides SQL, you can choose between R or Python to learn.
It helps to browse jobs you’re interested in. The listings can give you an idea of which programming language to choose, as well as which visualization tools to familiarize yourself with.
Employers always look for two things: knowledge and experience. By going through the above steps, you’ll get the necessary foundation to become a data analyst. But you won’t have any experience at all, meaning that at this point, employers will overlook your application still.
Those already enrolled in degree programs or online courses will likely get the opportunity to take on projects with real data sets. For the self-taught, you can find free public data sets to use on your own projects. Some organizations to try include:
- DataCamp Workspace
- Google Dataset Search
- National Centers for Environmental Information
- UCI Machine Learning Repository
Creating projects from scratch will certainly be impressive to potential employers, so find something you’re passionate about to really shine.
Whether you’re completing assignments in class or working on your own projects (or both!), keep good track of your work. Employers will want to see your portfolio since it proves you have an excellent foundation in data analysis.
Over time, you may accumulate numerous projects under your belt. In that case, select your best projects to present to potential employers. Avoid ones that everyone else has done; focus on your passions and interests instead. If you have them, make sure to pick group projects too, as they prove that you can work well in a team.
Another idea is if you know which companies you want to work at, you can make projects that are related to their niche. When these businesses see that you’ve taken the initiative to learn about them and what they do, they’ll view you favorably against the competition.
In addition to a portfolio, you should have a resume too. It should be short and to the point, no longer than one page.
List your relevant experience, as well as education. In addition, put down the projects you’ve worked on.
If you’re struggling, search online for resume templates. You can also utilize resume help services from specialized sites like LinkedIn.
Check your resume thoroughly for errors. If that makes it through the employer will reflect poorly on you, and they’ll throw out your application right away.
Now that you’ve gotten everything in order, it’s time to apply for entry-level data analysis jobs. A good place to start is LinkedIn, where you can also create a professional profile to attract headhunters. Other places to try include:
- Google for Jobs
- Well found
It wouldn’t hurt to approach businesses first. You might be rewarded for being proactive.
In any case, you should tailor your resume for every job application. Read the job description and confirm that you’re the right person for the job by reiterating what they’re looking for.
After you’ve successfully landed a job as a data analyst, you probably won’t stay as an entry-level employee for long. If you work hard and prove your talent, you can move up in a company.
However, you can make this process quicker by getting certifications or an advanced degree. For example, as a Certified Analytics Professional, you can earn a higher salary.
Data analysis is a field that’s here to stay. While some people might find it tedious, you might find it fascinating and a viable career change.
It may take some work, especially if you don’t have a relevant background already. But in the end, it’ll pay off when you can work in a stable and highly rewarding job that gives ample opportunities for you to move up in a business.
Check out the rest of our blog page for more career advice.