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Data Analyst Roadmap

How to become a Data Analyst, phase by phase: what you do in each one, how long it takes, and the proof that shows you're done.

5 phases11–23 months15 resources

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The road, phase by phase

  1. Phase 1: Drilling Sql and Spreadsheets

    1–2 months

    Working daily through SQL exercises (joins, aggregations, window functions) and spreadsheet skills like pivot tables and lookups on sample datasets. By the end, the person can pull and summarize data from a relational database without looking up syntax.

    You're done when you can show

    A GitHub repo or profile showing 50+ solved SQL problems (e.g. LeetCode, StrataScratch).

    Resources

  2. Phase 2: Learning Python and Statistics

    1–2 months

    Shifting from querying to manipulating data in Python with pandas, while learning descriptive statistics, distributions, and hypothesis testing. The person produces notebooks that clean messy data and answer simple statistical questions.

    You're done when you can show

    A public notebook cleaning a messy dataset and running a statistical test.

    Resources

  3. Phase 3: Building End-to-end Portfolio Projects

    2–3 months

    Picking real public datasets, framing business questions, analyzing them, and building dashboards in Tableau or Power BI with written recommendations. The output is 2–3 polished projects that show the full workflow from question to insight.

    You're done when you can show

    A portfolio link with 2–3 projects, each including a live dashboard and write-up.

    Resources

  4. Phase 4: Applying and Interviewing for Roles

    1–4 months

    Tailoring a resume around the portfolio, networking with analysts, sending applications, and practicing SQL screens, take-home assignments, and case interviews. This ends with a signed offer for an analyst or analyst-adjacent position.

    You're done when you can show

    A signed offer letter for a data analyst role.

    Resources

  5. Phase 5: Delivering Analyses for Stakeholders

    6–12 months

    Working inside a company's real data stack, learning the business domain, answering stakeholder requests, and owning recurring reports and dashboards. The person proves they can turn ambiguous business questions into analyses that drive decisions.

    You're done when you can show

    A production dashboard or analysis you own that stakeholders use for a decision.

    Resources

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