Data Analyst Roadmap
Follow this sequence to build a strong, hirable profile. Complete each step before moving to the next.
Excel mastery
VLOOKUP, pivot tables, charts, data validation, and basic statistical functions
SQL proficiency
SELECT, JOINs, GROUP BY, window functions, subqueries, and query optimisation
Python for data
pandas for data manipulation, NumPy for computation, and Jupyter notebooks
Data visualisation
Matplotlib, Seaborn, and Tableau or Power BI for business dashboards
Statistics foundations
descriptive stats, probability, distributions, hypothesis testing, and A/B testing
Data cleaning
handling null values, outliers, duplicates, type conversion, and data validation
Business context
understanding KPIs, metrics, funnel analysis, cohort analysis, and churn analysis
Storytelling with data
structuring insights for non-technical stakeholders, executive-ready reports
Introduction to machine learning
linear regression, classification, clustering using scikit-learn
Build a portfolio
3 end-to-end projects from data collection to insight presentation on GitHub or Tableau Public
Use AI Career Hub tools as you progress
Build your resume at each stage, generate interview questions for each skill, and practice mock interviews to track your readiness.
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