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How to Become a Data Analyst

A no-degree-required path, in five phases you can actually finish.

You do not need a computer-science degree or a bootcamp loan to become a data analyst. You need three demonstrable skills — SQL, statistics, and turning numbers into a decision — plus a small portfolio that proves them. This roadmap orders that learning so each phase builds on the last, and points only at resources that are genuinely free to start.

Who this is for: Students, career-switchers and anyone self-teaching from scratch. It assumes no prior coding.

  1. 1 · Spreadsheets and data thinking

    Learn to clean, shape and reason about data before touching code.

    Excel / Google SheetsPivot tablesVLOOKUP / XLOOKUPBasic chartsData cleaning

    You're ready when

    You can take a messy exported sheet, clean it, and answer a question with a pivot table and a chart.

    Practise on the CSV Cleaner →

  2. 2 · SQL — the non-negotiable skill

    SQL is on essentially every analyst job description. This is where most of your time should go.

    SELECT / WHERE / ORDER BYGROUP BY & aggregatesJOINsSubqueries & CTEsWindow functions

    You're ready when

    You can write a query with a JOIN, a GROUP BY and a window function to answer a business question without looking up the syntax each time.

    Practise with SQL case studies →

  3. 3 · Statistics that actually get used

    Not a stats degree — the working subset: distributions, averages that don't lie, and testing.

    Descriptive statisticsDistributionsCorrelationHypothesis testingA/B testing basics

    You're ready when

    You can explain the difference between mean and median to a stakeholder, read a p-value honestly, and say when a result is too small to trust.

    Try the A/B Test Calculator →

  4. 4 · Visualisation, BI and a portfolio

    Turn analysis into something a decision-maker acts on — and prove you can, publicly.

    Tableau or Power BIChart choice & designDashboardsStorytelling with data2–3 portfolio projects

    You're ready when

    You have 2–3 finished projects online, each with a question, the SQL/analysis, a visual and a written takeaway.

    See portfolio project ideas →

  5. 5 · The job search

    Target analyst-specific roles, tailor to each posting, and apply where the competition is thinner.

    Analyst-focused resumeMatching skills to the JDCover note / outreachInterview prep

    Free resources

    You're ready when

    Your resume names the same skills the job description does, and you are applying to real analyst roles — not generic 'data' listings.

    Match your resume to a job →

Frequently asked

How long does it take to become a data analyst?
With consistent part-time study, most self-learners reach a portfolio-ready level in roughly 4–8 months. The variable is not intelligence, it is finishing projects — the SQL and stats are learnable in weeks; the portfolio and job search take the rest.
Do I need a degree?
No. Plenty of analysts come from non-technical degrees or none at all. Employers hiring analysts care about demonstrable SQL, a portfolio and clear communication far more than the subject on your diploma.
Do I need to learn Python?
Not to start. SQL, spreadsheets and a BI tool are enough for most entry-level analyst roles. Python helps and opens more doors later, but leading with it before you are fluent in SQL is the common mistake.
Is the Google Data Analytics certificate worth it?
As a structured starting point for a complete beginner, it is reasonable. As a hiring signal on its own, it is weak — a certificate is common, a portfolio of real analysis is not. Treat it as a syllabus, not a finish line.

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