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Data Analyst Roadmap — From Beginner to Hireable

Data analyst roadmap from beginner to hireable: SQL, statistics, Python analysis and presenting findings. Kaidoro adapts it to your background and deadline.

Starting level: beginner8h / week4 phases

This is a starting point — make it yours

Use this goal to build your own roadmap — tailored to you and starting fresh.

1

SQL

The single most-used skill in the job.

  • Learn SQL to an interview standard~20h

    Joins, aggregation, subqueries, window functions, CTEs. Window functions are what separate junior from mid.

    Done when: you can write a running total and a rank within groups from memory.

  • Analyse a messy real dataset~12h

    Find one on Kaggle with genuine problems — missing values, duplicates, inconsistent categories. Clean it and document every decision.

    Done when: someone else could reproduce your cleaning from your notes.

2

Statistics that matter

Enough to avoid confidently reporting noise.

  • Learn descriptive and inferential statistics~14h

    Mean vs median, variance, distributions, sampling, confidence intervals, p-values and what they don't mean.

    Done when: you can explain why a p-value isn't the probability the hypothesis is true.

  • Run and interpret an A/B test~10h

    Set up the hypothesis, work out the sample size, run the test, decide honestly.

    Done when: you can say 'this result is not significant' and defend it.

  • Learn regression as an explanatory tool~12h

    Linear and logistic regression for understanding relationships, not just prediction. Interpret coefficients.

    Done when: you can explain what a coefficient means in plain English.

3

Tools and visualisation

How the work gets done and shown.

  • Get fluent with Python for analysis~16h

    Pandas for manipulation, matplotlib or seaborn for charts, Jupyter for exploration.

    Done when: you can go from CSV to a clear chart in ten minutes.

  • Learn to build charts that don't mislead~8h

    Choosing the right chart, truncated axes, colour that survives colourblindness, labelling.

    Done when: you can explain why a dual-axis chart is usually a bad idea.

  • Build a dashboard~12h

    Power BI, Tableau or Streamlit. Make it answer a specific question rather than showing everything.

    Done when: a stakeholder can answer their question without asking you.

4

Communicate it

The part that gets analysts promoted.

  • Write up an analysis end to end~10h

    Question, method, findings, limitations, recommendation. Lead with the answer, not the method.

    Done when: a non-technical reader knows what to do after the first paragraph.

  • Build a portfolio of three analyses~20h

    Different domains, different techniques. Public, readable, with the code available.

    Done when: each one stands alone without you narrating it.