How do you learn data analysis from zero?
Start with spreadsheet basics and SQL, then learn Python and visualization, and practice on real datasets. DataCamp has the most focused learning path for this; the Google Data Analytics certificate via Coursera is the best route toward a job.
Data analysis is one of the most in-demand and most learnable digital skills: the route is clear and practice material is endless. The order that works: data thinking in spreadsheets first (filters, pivot tables, charts), then SQL to pull data from databases (the most requested data skill in job ads), then Python with pandas for serious analysis, and visualization to communicate findings.
DataCamp is the most targeted platform for this route: interactive tracks per step, coding in the browser, and projects on real datasets. Codecademy is the good alternative with a broader programming base. If you want to stack it toward a job, the Google Data Analytics Professional Certificate on Coursera is the best-known entry credential, built for people without a background in the field.
The key here too is doing: after each course phase, find your own question in an open dataset (government data, sports stats, your own usage data) and write it up briefly. Three such projects are a portfolio, and portfolios open doors.