SQL for Analytics

What you will learn

• Choose the right grain for fact and dimension style queries
• Use joins and window functions to answer common product questions
• Build cohort and retention style analyses safely
• Document metric definitions so stakeholders share one meaning
• Spot freshness and null-handling issues before publishing a dashboard

About this course

Analytics work fails when queries are hard to trust. This course teaches analysts and engineers how to shape tables, write readable SQL, and define metrics that survive scrutiny from finance and product leaders. You will practice joins, window functions, cohort patterns, and metric definitions. We also cover documentation habits: naming, grain, and freshness so dashboards do not silently lie. The tone is practical. Bring a real question from your product and leave with a query pattern, not just syntax notes.

Who it is for

• Analysts supporting product and growth teams
• Engineers who occasionally own reporting queries
• PMs who want to read and challenge SQL outputs