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Data Analyst Roadmap

Become a data analyst who turns messy data into clear, actionable business insights. One of the most accessible entry points into the data field — no PhD required.

4-6 months3-6 LPA → 18-35 LPA expected9 steps • 29 free resources
1

Excel & Google Sheets Mastery

2-3 weeks

Excel is still the most-used data tool in Indian companies. Master pivot tables, VLOOKUP, conditional formatting, and data cleaning before anything else.

By the end, you'll be able to

  • Build pivot tables and dashboards in Excel/Sheets
  • Use VLOOKUP, INDEX-MATCH, and conditional formulas
  • Clean and transform messy data efficiently
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Mini-project

Analyze a sales dataset in Excel: create a dashboard with pivot tables showing revenue by region, product, and month. Add slicers for interactivity.

2

SQL for Analysis

3-4 weeks

SQL is the #1 skill for data analysts. Learn SELECT, JOINs, GROUP BY, window functions, CTEs, and how to extract insights from databases.

By the end, you'll be able to

  • Write production-level SQL queries with complex JOINs and aggregations
  • Use window functions for running totals, rankings, and comparisons
  • Extract business KPIs directly from a database
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Mini-project

Solve 40 SQL problems on HackerRank/LeetCode. Then write queries to answer 10 business questions on a sample dataset.

3

Python for Data Analysis

3-4 weeks

Python automates what Excel can't. Learn Pandas for data manipulation, Matplotlib/Seaborn for visualization, and Jupyter notebooks for analysis workflows.

By the end, you'll be able to

  • Manipulate dataframes with Pandas: filter, group, merge, pivot
  • Create publication-quality charts with Matplotlib and Seaborn
  • Automate repetitive data tasks with Python scripts
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Mini-project

Analyze the Swiggy or Zomato restaurant dataset: pricing trends, ratings by cuisine, delivery times. Create 10 insightful visualizations.

4

Statistics for Business

2-3 weeks

Learn the stats that matter for analysis: averages, distributions, correlation, hypothesis testing, and A/B testing. Skip the theoretical proofs — focus on practical application.

By the end, you'll be able to

  • Interpret distributions, correlations, and outliers in business data
  • Run and interpret A/B tests for product decisions
  • Communicate statistical findings without jargon
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Mini-project

Analyze an A/B test from a sample e-commerce dataset. Present your findings as a 1-page business memo.

5

Tableau / Power BI

2-3 weeks

Dashboards are how analysts communicate. Learn one BI tool deeply: connecting data, building charts, creating interactive dashboards, and publishing them.

By the end, you'll be able to

  • Build interactive dashboards with calculated fields and filters
  • Connect multiple data sources and create relationships
  • Design dashboards that tell a story and drive action
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Mini-project

Build a COVID-19 India dashboard in Tableau Public: state-wise trends, vaccination progress, and recovery rates. Publish it.

6

Data Cleaning & ETL

1-2 weeks

80% of analysis is cleaning data. Learn to handle missing values, duplicates, inconsistent formats, and how to build reliable data pipelines.

By the end, you'll be able to

  • Clean messy real-world datasets systematically in Python
  • Handle missing values, duplicates, and data type issues
  • Build simple ETL pipelines to automate data preparation
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Mini-project

Take a deliberately messy dataset and clean it: fix dates, handle nulls, remove duplicates, standardize categories. Document every step.

7

Business Metrics & KPIs

1-2 weeks

Know what to measure. Learn common business metrics: CAC, LTV, churn, retention, conversion funnels, unit economics, and how to track them.

By the end, you'll be able to

  • Define and calculate key business metrics for any company
  • Build funnel analyses and cohort analyses
  • Create metric dashboards that executives actually use
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Mini-project

Build a product analytics dashboard for a fictional SaaS company: MRR, churn, DAU/MAU, funnel conversion, and cohort retention.

8

Portfolio Projects

3-4 weeks

Build 3 analysis projects that showcase your skills: one with SQL, one with Python, one with a BI tool. Write clear narratives explaining your insights.

By the end, you'll be able to

  • Complete 3 end-to-end analysis projects with clear business insights
  • Write compelling project narratives that non-technical people understand
  • Publish your work on GitHub, Tableau Public, or a portfolio site
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Mini-project

Create a portfolio with 3 projects: (1) SQL analysis of an e-commerce dataset, (2) Python EDA of a public dataset, (3) Tableau dashboard of Indian economic data.

9

Interview Prep

2-3 weeks

Data analyst interviews test: SQL (heavy), Excel, statistics, case studies, and behavioral questions. SQL is the most important — practice it daily.

By the end, you'll be able to

  • Ace SQL interview questions including window functions and CTEs
  • Walk through a case study with structured analytical thinking
  • Present your projects concisely and highlight business impact
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Mini-project

Solve 50 SQL problems, practice 5 case studies, and do 2 mock interviews. Apply to 20+ analyst roles.

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Pick the path that fits you

Not sure if this is the right roadmap? Browse all our career paths and find the one that matches your goals.