As a self-taught data analyst who pivoted from another industry, I sometimes get asked what it takes to get a foot in the door as a junior. It seems like there are a lot of opportunities for experienced candidates, but not many for true juniors unless they come from analytics programs.
With a bit of learning and a lot of practice, you don’t need to go back to school full-time to land an interesting job in data analytics.
To get a job as a data analyst, you need to focus on the most important skills - think of the 80/20 principle, with SQL really being the 20% you need to achieve 80% results.
Learn SQL
SQL is a data analyst’s Swiss army knife. On top of letting you retrieve information from a database, mastering SQL will allow you to understand existing code, debug queries upon discovering an issue with the data, and perform complex calculations. You don’t have to know window functions by heart, but knowing they exist and their role will definitely help. What you really need is to be able to write clean SQL code, know basic functions, and especially how to use them. There are many ways to achieve this and several slightly different versions of SQL, but they are functionally identical to each other. You can find a lot of good datasets online to start practicing, for instance at Kaggle.
Familiarize yourself with a data pipeline
SQL proficiency goes beyond coding, as it means understanding simple data architecture and how the data cycle works, how data is generated, transformed, and stored before it can be aggregated and analyzed.
Get experience with dashboarding tools
On top of that, basic knowledge of dashboarding is a huge plus, as most of an analyst’s work consists of building dashboards to allow non-technical teams to access their data. Being able to display data visually as an efficient narrative will bring you a long way.
Understand simple command line, Git, and Python basics
Once you are comfortable with the basics, there are of course some nice skills to have: simple command line, knowing how to use Git, some Python. However these should not be your main focus, and you can pick them up quickly if you master SQL and a visualization tool.
Be experienced with spreadsheet software
A skill I did not mention because it is often a given - is a spreadsheet software. While you don’t need to be an Excel wizard to be a data analyst, you will often need to extract data and process it on Excel/Gsheet, either for your own use or for others who do, so the return on investment for knowing the basics is major.
Develop an understanding of what data means to your business
Companies also evaluate candidates on their business sense, as an analyst needs to advise stakeholders on KPI creation and offer solutions based on business value. More generally, understanding the broader significance of the data you are processing and how it relates to a company’s product and main initiatives is very important.