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Become a Data Analyst

Data Analyst

A structured path into entry level data analyst roles: SQL, spreadsheets, Python, dashboards and the projects recruiters ask about.

Get a personalised planSee the 4-course path

What a Data Analyst does

A data analyst collects, cleans and studies data to answer business questions. A typical day includes writing SQL queries, checking data quality, building or updating dashboards, and explaining findings to people who are not technical.

The role suits students from any branch who enjoy working with numbers and explaining them clearly. Many freshers enter through analyst, MIS or reporting roles before moving into business or product analytics.

Skills and tools

Skills you need

  • SQL: joins, grouping, subqueries and window functions
  • Spreadsheet modelling with lookups and pivot tables
  • Python for data work with pandas
  • Data cleaning and validation
  • Descriptive statistics
  • Dashboard design and storytelling
  • Clear written and spoken communication

Tools you will use

  • Microsoft Excel or Google Sheets
  • MySQL or PostgreSQL
  • Python with pandas and Matplotlib
  • Power BI or Tableau
  • Jupyter Notebook
  • Git and GitHub

Your path, in order

  1. Data Analytics with Python: BeginnerBeginner · 8 weeks · CertificateGo from zero to your first data driven report: Python, SQL, statistics, dashboards, and a Generative AI powered reporting feature.
  2. Business Analytics: BeginnerBeginner · 8 weeks · CertificateGo from zero to your first business decision backed by data: Excel, SQL, statistics, dashboards, and a live boardroom presentation.
  3. Data Analytics with Python: IntermediateIntermediate · 8 weeks · CertificateGo from analyst to insight driven professional: advanced SQL, experimentation, cohort and forecasting analysis, and Generative AI over business data.
  4. Data Analytics with Python: AdvancedAdvanced · 8 weeks · CertificateFrom analyst to analytics architect: analytics engineering, big data pipelines, causal inference, advanced forecasting, and production Generative AI analytics.

Projects to build

  • Sales performance dashboard

    Build a dashboard on a public retail dataset that shows revenue by region, month and category, and write three insights a manager could act on.

  • SQL business case study

    Answer ten business questions from one dataset using SQL, and publish the queries with a short explanation of each result.

  • Data cleaning notebook

    Take a messy public CSV, document every cleaning step in Python, and show the before and after quality checks.

What interviews cover

  • Joins, group by and window functions
  • Handling missing and duplicate data
  • Mean, median, variance and outliers
  • Explaining a dashboard to a non technical audience
  • Excel lookups and pivot tables
  • Walking through one of your projects end to end

Not sure where you are on this path?

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For becoming a Data Analyst

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Frequently asked questions

No. Employers mainly look for SQL, spreadsheet and analysis skills, and projects that show you can use them. Students from any branch can build these.

Start with SQL and spreadsheets, then add one visualisation tool and Python. SQL appears in most analyst interviews.

Two or three well documented projects that you can explain in detail are more useful than many small ones.

Search for data analyst, business analyst, MIS analyst, reporting analyst and junior analyst roles.