Key takeaways
- The plan assumes about one to two hours of study per day.
- Months 1 to 4 build tools: Excel, SQL, statistics and Power BI.
- Month 5 adds Python and a capstone project.
- Month 6 is for portfolio, resume, mock interviews and applications.
- Revision weeks are built in so that older topics are not forgotten.
What is data analyst 180-day roadmap?
Who is this plan for?
The 180-day plan fits students and working people who can give one to two hours a day, including some weekend time. If you can study full time, the 90-day plan is faster. The schedule is a guide: if a topic takes longer, use a buffer week and keep going.
What does month 1 cover?
Weeks 1-2: data basics and Excel: tables, sorting, filtering, formulas, text and date functions. Week 3: lookups, SUMIFS, COUNTIFS and PivotTables. Week 4: charts, a mini dashboard and revision. Goal: clean and summarise a 1,000-row sheet and explain it.
What does month 2 cover?
Weeks 5-6: statistics basics: mean, median, spread, correlation, sampling. Weeks 7-8: SQL basics: SELECT, WHERE, ORDER BY, GROUP BY, HAVING and aggregates. Goal: answer ten questions on a sample database.
What does month 3 cover?
Weeks 9-10: joins, subqueries and CTEs. Week 11: window functions. Week 12: SQL project and revision. Goal: a SQL project with a written summary of the queries and findings.
What does month 4 cover?
Weeks 13-14: Power BI: loading data, Power Query cleaning, the star schema. Weeks 15-16: DAX measures, visuals, slicers and a finished dashboard. Goal: a two-page dashboard with four KPIs and a short user note.
What does month 5 cover?
Weeks 17-18: Python basics and pandas: load, clean, group and merge. Week 19: charts with Matplotlib or Seaborn. Week 20: the capstone: choose a dataset, ask a question, clean, analyse, chart and write up. Goal: one end-to-end project.
What does month 6 cover?
Week 21: portfolio: polish three projects and write readme files. Week 22: resume and profile; write project bullets. Week 23: interview practice: SQL tasks, Excel tasks, a case question and project stories. Week 24-26: applications, mock interviews and revision of weak topics.
How do I stay on track?
| Habit | How |
|---|---|
| Daily slot | Same time each day, even 45 minutes |
| Weekly review | Sunday: list what you learned and what is weak |
| Monthly project | Finish a small output every month |
| Buffer weeks | Use them when a topic runs long |
| Accountability | Study with a friend or post weekly progress |
What if I fall behind?
Skip nothing in SQL and statistics, since they are used everywhere, but shorten extras such as advanced chart types. Move the date of the capstone before moving the date of mock interviews. A smaller finished plan is better than a perfect plan abandoned.
What results can I expect?
You can expect a working skill set in Excel, SQL, Power BI and basic Python, and three to four projects to show. The plan does not promise a job or a salary; hiring depends on the market, your portfolio and your interview performance.
How should I split a daily session?
Use a simple pattern: twenty minutes of review, forty minutes of new learning and thirty minutes of practice. On project days spend the whole session on the project and write a short note at the end. Keep a daily log with the topic, the minutes studied and one question to answer tomorrow. After four weeks the log shows your real pace and helps you adjust the plan.
Which checkpoints tell me I am ready to move on?
At the end of month one you should build a PivotTable summary without help. At the end of month three you should write a join and a window function from memory. At the end of month four you should publish a dashboard with three measures. At the end of month five you should clean a messy CSV in pandas. If you miss a checkpoint, use a buffer week before moving on.
What should I do in the last weeks?
Apply to roles that match your skill level, tailor your resume for each, send a short note with a project link and keep practising SQL and Excel tasks. After each interview, write down what was asked and improve. Keep building a small project at the same time so that your portfolio keeps growing.
How do I measure progress each month?
At the end of every month, redo a task from the start of that month without help and compare the time taken. Write one paragraph about what improved and what is still weak. These monthly notes also give you material for interviews, because you can describe how you learn.
Download Data Analyst 180 Day Roadmap PDF
Data Analyst 180 Day Roadmap PDF
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