Anthropic's data work is API-usage analytics at scale: cohorts, retention, percentile usage, and event streams that need dedup before they mean anything. Practice those SQL shapes on runnable datasets with AI tutoring.
20 challenges
Anthropic-pattern set
Real datasets
API-usage-shaped tables
AI tutor
Step-by-step hints
The 20 challenges tagged Anthropic in the SQL Quest bank, with every raw challenge tag resolved to the 9 canonical skills. Each share is the portion of those 20 challenges that exercise the skill — a challenge exercises several, so the shares do not sum to 100%. This is the composition of the practice set on this page, not a measurement of Anthropic’s interview.
These are SQL Quest challenges chosen because their SQL matches the work — Querying Basics, Window Functions, Aggregation & Grouping. They are not questions Anthropic has asked, and this page does not claim to know its questions. All of the six play free; each card opens the challenge itself.
General guidance about analytics SQL work — not sourced from Anthropic and not a description of its process. We have no dated, citable source for how Anthropic runs its SQL round, so this page states none.
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Interviewing at more than one company? The same patterns carry: OpenAI · NVIDIA · Databricks — or the full company-by-company interview guide.