Data Analyst

Data Analyst roadmap

Follow the line, from first step to goal.

1. 1

   Spreadsheets (Excel/Sheets)

   Start

   Spreadsheets are the simplest tool for looking at data, sorting it, and doing quick calculations. Start here before anything more advanced.

2. 2

   SQL — talking to databases

   A language for asking a database questions, like 'show me all orders from last week.'

3. 3

   Statistics basics

   Averages, percentages, and how to tell if a pattern in data is real or just chance.

4. 4

   Data cleaning

   Real-world data is messy. You need to fix typos, missing values, and duplicates before you can trust any analysis.

5. 5

   Python or R for analysis

   A programming language that lets you analyze bigger datasets faster than a spreadsheet can.

6. 6

   Data visualization

   Turning numbers into charts and graphs so people can understand your findings at a glance.

7. 7

   Dashboards (Tableau/Power BI)

   Tools that turn your analysis into a live, clickable report other people can check anytime.

8. 8

   Storytelling with data

   Explain what the numbers mean in plain language. Don't just show charts and hope people understand.

9. 9

   Git & version control basics

   Keeping track of changes to your analysis files, especially useful once you work with others.

10. Working with real business questions

    Goal

    Practice on real problems, like deciding which product to promote. Use all the tools above from start to finish.