Intro to Data Analytics
The essentials: questions over queries, value over vanity metrics, and where SQL/Python fit.
Clear tutorials, real cases, and ready-to-share snippets for SQL, Python, BI and data storytelling. Built for analysts, leaders, and the analytics-curious.
The essentials: questions over queries, value over vanity metrics, and where SQL/Python fit.
Curiosity, business thinking, healthy scepticism, and data storytelling — the four habits that change careers.
A mini-playbook: define the decision, test assumptions, build a narrative, ship a one-page brief.
A one-page visual from question → data → analysis → decision → impact — perfect for workshops.
We simplify analytics for everyone from beginners to professionals. A practical, example-led curriculum that moves from questions to impact.
From joins to cohorts write queries that mirror business questions like churn, retention, and growth funnels.
Use pandas the business-savvy way: tidy inputs, test assumptions, and ship artefacts stakeholders love.
Structure the narrative: setup, conflict, resolution, call to action. Use a one-page brief and a two-slide storyboard.
Practical explainers and examples designed to be shared with teams and stakeholders.
The best analysts aren’t defined by Python or Power BI. They’re defined by how they think: curiosity, business focus, scepticism, and storytelling.
An easy cohort query you can paste into your warehouse to reveal week-on-week retention.
WITH first_orders AS ( SELECT user_id, MIN(order_date)::date AS cohort_date FROM orders GROUP BY 1 ), orders_by_week AS ( SELECT o.user_id, DATE_TRUNC('week', o.order_date)::date AS order_week, f.cohort_date FROM orders o JOIN first_orders f USING (user_id) ) SELECT cohort_date, order_week, COUNT(DISTINCT user_id) AS active_users, ROUND(100.0 * COUNT(DISTINCT user_id) / NULLIF(MAX(COUNT(DISTINCT user_id)) OVER (PARTITION BY cohort_date),0), 1) AS retention_pct FROM orders_by_week GROUP BY cohort_date, order_week ORDER BY cohort_date, order_week;
A pragmatic checklist for acquisition and retention teams and a one-slide model you can share.
Ask questions, get feedback, and share what you’re building.
Weekly prompts and teardown threads on data stories and dashboards.
Hands-on builds and real-world examples.
One actionable analytics idea each week — concise and practical.