A data analyst is someone who collects, cleans, and studies data to find patterns and insights that help organisations make better decisions. It is one of the most in demand and accessible careers in tech right now, partly because you can enter it from many backgrounds, including commerce, science, and even arts, as long as you build the right skills. You do not necessarily need a computer science degree.
The core skills are a comfort with numbers and logic, plus a set of practical tools. Start with Excel or Google Sheets, which are still widely used, then learn SQL for pulling data from databases, since almost every analyst job needs it. Add a data visualisation tool like Power BI or Tableau to present findings clearly, and learn the basics of a language like Python or R for deeper analysis. A grasp of basic statistics helps you interpret data correctly rather than just describing it.
In terms of path, you can take a relevant degree such as statistics, maths, economics, computer science, or commerce, but many analysts also come through focused online courses and certifications, because employers care a lot about proven skills. The most important thing is to build real projects using public datasets and put them in a portfolio, because showing that you can actually analyse data and tell a story with it matters more than certificates alone. Start with small projects, get comfortable with the tools, and apply for entry level analyst or junior roles and internships to get in. The field rewards continuous learning, so keep sharpening your skills as tools evolve.
Example: A commerce student who learns Excel, SQL, and Power BI, then builds two or three portfolio projects analysing real datasets, can realistically apply for junior data analyst roles.
One practical tip: Build a portfolio of real projects using free public datasets. Demonstrated skill on actual data opens more doors than certificates on their own.