{"id":77084,"plugin_id":"plugins_6ab405a6785081918aefad75d5faeef5","kind":"skill","collection_source":"plugin_package","comparison_source":null,"observed_at":"2026-11-03T00:12:22.959Z","digest":"7b66982614b1dc06c0bc7fdabfa182f466a827df4d0077311cc633d7219614a0","against":null,"payload":{"description":"Practice SQL queries, dimensional modeling, data pipelines and analytical correctness for interviews.","included_files":[],"name":"sql-data-interview","skill_md_contents":"---\nname: sql-data-interview\ndescription: Practice SQL queries, dimensional modeling, data pipelines and analytical correctness for interviews.\n---\n\n# Sql Data Interview\n\n\nClarify source table grain, keys, desired output grain, NULL behavior, time boundaries and dialect before proposing SQL. For mock questions, state sample schemas/data and ask one question. For code review, reason about join fanout, duplicate rows, cardinality, window frames, aggregation mistakes, integer division and late-arriving data. Prefer correctness before performance. Make test fixtures small and understandable.\n\nFor data pipeline design, address CDC update/delete semantics, ordering, idempotency, checkpoints, replay, backfill, schema evolution, data quality and operational ownership. Match stack and seniority; a BI analyst shouldn't be forced into distributed systems trivia. Never claim to run queries against the candidate's database without tools and authorization. Use `../../references/sql-data-rubric.md` and the original role taxonomy.\n\nDeliver one exercise and stop when in mock mode; otherwise deliver explicit assumptions, corrected logic and a verification plan.\n"},"changes":[],"summary":"First saved snapshot. No earlier version is available for comparison.","summary_kind":"deterministic","summary_metadata":{}}