Data Analyst
A research-backed roadmap from zero to job-ready across 8 stages — SQL, Python, Statistics, Visualisation, AI tools, and the modern data stack in the exact dependency order.
Foundations
2–3 weeksMental models, business vocabulary, and the data mindset before you write a single query — now with AI literacy built in.
SQL
4–6 weeksThe single most universal analyst skill — in 80%+ of all job postings. DuckDB and cloud SQL dialects now matter alongside standard SQL.
Python for Analysis
6–8 weeksPolars and DuckDB join pandas as mainstream tools in 2026. Marimo notebooks are replacing Jupyter for shareable work.
Statistics & Analytics
4–5 weeksWhat separates analysts who pull numbers from those who generate genuine business insight. CUPED, sequential testing, and causal inference are 2026 must-knows.
Data Visualisation
3–4 weeksGenerating insights is half the job. Communicating them clearly to non-technical stakeholders is the other half. Tableau Pulse and Power BI Copilot have changed what BI looks like in 2026.
AI & Modern Tools
2–3 weeksThe AI-native analyst is now the baseline, not the exception. Cursor, Julius AI, and ChatGPT ADA are production tools in analyst workflows.
Cloud & Data Stack
3–4 weeksApache Iceberg is now the industry standard open table format. dbt MetricFlow + Semantic Layer is how metrics are governed in 2026. MotherDuck brings DuckDB to the cloud.
Portfolio & Career
4–8 weeksIn a competitive market, skills are necessary but not sufficient. AI-augmented portfolio projects and demonstrated tool fluency get you hired in 2026.
Ready to start your path?
SQL is the single highest-ROI first step — in 80% of all data analyst job postings.