SQL Practice Tracks
Use practice to move from syntax knowledge to query fluency.
This section has three modes:
- Skill Drills: short targeted exercises (easy → hard)
- Timed Tracks: speed-focused autograded sprints (10/20/30 min)
- Industry Tracks: realistic datasets and business-style assignments
Which track fits your goal?
- Building fluency from scratch → start with Skill Drills (SQL Core 10-Exercise Track first).
- Prepping for a timed interview/screen → use Timed Tracks after you can comfortably finish the Core 10.
- Portfolio-building / job applications → go straight to an Industry Track (insurance, e-commerce, or SaaS) and finish with the capstone.
Skill Drills #
Start with:
Timed Tracks #
Start with:
Industry Track: Insurance Analytics #
Eight pages from schema to capstone: premiums, claims, loss ratios, and claims aging. Start with the Insurance Track Overview, then follow its flow: star schema → meet the dataset → data quality audit → graded drills → KPI assignments → loss ratio trends → capstone.
Industry Track: E-commerce Analytics #
Orders, returns, customer value, and conversion. Start with the E-commerce Track Overview, then follow its flow: star schema → meet the dataset → data quality audit → graded drills → KPI assignments → RFM segmentation → funnel analysis → capstone.
Industry Track: SaaS Analytics #
MRR, churn, net revenue retention, and the MRR bridge. These are the metrics every SaaS analytics interview asks about. Start with the SaaS Track Overview, then follow its flow: star schema → meet the dataset → graded drills → KPI assignments → capstone.
Common Mistakes and Next Step #
Common mistakes:
- jumping to complex joins before validating row counts and grain assumptions
- finishing a query without basic validation checks against expected totals
Next step:
- choose one track and complete the first two drills in sequence before switching tracks.
- not sure where to begin? start with the SQL Core 10-Exercise Track.
Recommended flow:
1) Solve with LIMIT and small selects first
2) Validate row counts at each step
3) Then optimize and clean up query shape