# SQL Analytics Workflow

> Design, review, debug, or explain analytical SQL with correct grain, joins, filters, time logic, performance awareness, and validation. Use for SQL analysis, writing or debugging a query, metric SQL, warehouse queries, cohorts, or database reporting. Turkish triggers: SQL analizi, sorgu yaz veya düzelt, veri modeli ve metrik mantığını doğrula.

- Skill: `yigityildiz0/sql-analytics-workflow` (Agent Skill)
- Install (CLI): `npx skillmds@latest add yigityildiz0/sql-analytics-workflow`
- Raw SKILL.md: https://api.skillmd.com/api/skills/yigityildiz0/sql-analytics-workflow/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Data & Analytics
- Author: yigityildiz0 (https://skillmd.com/u/yigityildiz0)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/yigityildiz0/sql-analytics-workflow

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# SQL Analytics Workflow

Make the question and row grain explicit before writing SQL.

1. Confirm dialect, tables, field meaning, row grain, time zone, and access boundaries.
2. Write a plain-language query contract: population, filters, joins, grouping, metric, and expected row count.
3. Build incrementally: inspect a small sample, validate joins, check duplicated entities, then aggregate.
4. Parameterize dates and document assumptions. Prefer safe read-only queries unless writes are explicitly authorized.
5. Validate totals against an independent small check and report limitations.

Do not execute destructive SQL, expose secrets, or assume dialect-specific functions. Flag PII and large-scan cost risks before execution.