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A data analyst helps a team decide something by turning data into an answer: which product sells best, why sign-ups fell, which city needs more stock. It is one of the most open routes into data for freshers, because the tools are friendly and you can start with a laptop. Here is a plan.
Formulas, pivot tables and clean layouts.
Joins, GROUP BY, window functions.
Power BI, Tableau or similar. Pick one.
Averages, medians, percentages, simple tests.
Cleaning and analysis on larger files.
What a data analyst does in a normal week
You receive a question such as why did orders drop last week. You find the right data, check that it is correct, write queries, make a chart or a table, and explain what you found and what the team could do. Much of the work is cleaning data and asking what the question really means. The skill that sets people apart is clear explanation, not only clever queries.
Skills to learn, in order
- Spreadsheets. Many teams still live in them. Learn formulas, lookups and pivot tables.
- SQL. The core tool. Start at SQL practice and the SQL for beginners guide, then learn joins and GROUP BY, then window functions.
- A dashboard tool. Learn one well. Make a dashboard with three to five charts that answer one question.
- Basic statistics. Mean and median, percentages, distributions, and what a sample is. Enough to avoid wrong conclusions.
- Python and pandas. For files too big or messy for a spreadsheet. See pandas for beginners and the data analysis track.
Build one project that tells a story
Choose a public dataset, such as sales, bike rentals or app reviews. Write a business question first, for example: which products should we stock more of before the festival season. Clean the data, answer the question with SQL, build a short dashboard, and end with a recommendation in plain words. Put it on GitHub with a README. See the GitHub portfolio guide.
Recruiters like projects that end with a decision, not only a set of charts.
What interviews ask
| Area | Example question |
|---|
| --- | --- |
|---|
| SQL | Find the top 3 products by revenue in each category |
|---|
| Statistics | What is the difference between mean and median, and when does it matter? |
|---|
| Case thinking | Sales fell 10 percent last month. How would you find out why? |
|---|
| Tools | How would you build a dashboard for a sales manager? |
|---|
| Communication | Explain this chart to someone who does not know data. |
|---|
For case questions, show a method: define the metric, check the data, break it down by time, region and product, form a guess and say how you would test it.
A 10-week plan
| Weeks | Focus |
|---|---|
| 1 to 2 | Spreadsheets and SQL basics |
| 3 to 4 | SQL joins, GROUP BY and window functions |
| 5 | A dashboard tool and basic statistics |
| 6 to 7 | Python and pandas basics |
| 8 | One project with a business question |
| 9 | Resume and GitHub. See the resume guide |
| 10 | Apply and practise case questions |
Where to apply
Look for data analyst, business analyst, reporting analyst and junior analyst roles. Many companies use these titles for similar work. Read the skills in each post and apply where your skills match. Analyst roles exist in banks, e-commerce, health, logistics and many other fields, so pick industries you find interesting. Use LinkedIn and referrals alongside job sites.
Where to start today
Find one public dataset you find interesting, and write the one business question you would like to answer with it.