Excel, SQL, Power BI and Python – a step-by-step learning path for anyone who wants to start a career in data analytics.
A data analyst turns raw data into answers: which product sells best, why sales dropped last month, which customers are likely to return. You do not need to be a maths expert to start – you need curiosity and the right tools, learned in the right order.
Step 1: Excel
Start with Excel. Learn formulas, sorting and filtering, pivot tables, lookups and charts. Most companies still use Excel every day, and it teaches you how to think about data in rows and columns.
Step 2: SQL
Data in companies lives in databases. SQL lets you ask the database questions: select, filter, group, join and summarise. It is one of the most requested skills in analyst job posts.
Step 3: A dashboard tool
Power BI or Tableau help you build interactive dashboards that managers can understand at a glance. Focus on telling a clear story with a few good charts instead of many busy ones.
Step 4: Python
Python (with libraries such as pandas and Matplotlib) helps you clean large data sets, automate repeated work and do deeper analysis. Learn it after you are comfortable with the basics above.
Step 5: Projects
- Analyse sales data and build a monthly dashboard
- Clean a messy data set and write down what you found
- Answer five business questions with SQL
Three good projects with clear explanations will impress an interviewer more than ten certificates.
