SQL Query Writer for Business Reports
Generate SQL queries for common business reporting needs — revenue trends, cohort analysis, funnel metrics, and more.
Prompt Template
You are a data engineer specializing in business analytics. Write SQL queries for the following report: Database: [PostgreSQL / MySQL / BigQuery / Snowflake] Report type: [e.g., monthly revenue by product, cohort retention, funnel conversion] Tables available: [list tables and key columns] Time period: [e.g., last 90 days, year-to-date] Filters needed: [e.g., only US customers, exclude test accounts] Grouping: [e.g., by week, by region, by plan tier] Metrics needed: [specific numbers you want] Provide: 1. The SQL query (with comments explaining key sections) 2. How to interpret the output 3. Any indexes that would speed up this query 4. A variation for month-over-month comparison
Example Output
Monthly Revenue by Product Tier — PostgreSQL
SELECT
DATE_TRUNC('month', o.created_at) AS month,
p.tier,
COUNT(DISTINCT o.customer_id) AS paying_customers,
SUM(o.amount_cents) / 100.0 AS revenue_usd,
ROUND(AVG(o.amount_cents) / 100.0, 2) AS avg_order_value
FROM orders o
JOIN products p ON p.id = o.product_id
WHERE
o.status = 'completed'
AND o.created_at >= DATE_TRUNC('year', CURRENT_DATE) -- YTD
AND o.test_mode = false -- exclude test accounts
GROUP BY 1, 2
ORDER BY 1 DESC, revenue_usd DESC;
**Interpretation:** Each row = one month + product tier combination. Compare `revenue_usd` across tiers to spot which tier drives growth.
Index recommendation:
CREATE INDEX idx_orders_created_status ON orders(created_at, status) WHERE test_mode = false;
MoM Comparison variation:
-- Add LAG() window function to compare with prior month
LAG(revenue_usd) OVER (PARTITION BY tier ORDER BY month) AS prev_month_revenue
Tips for Best Results
- 💡Share your actual table and column names — generic column names like 'amount' vs 'amount_cents' cause bugs
- 💡Ask for the query and then ask 'what edge cases could cause incorrect results?' — it catches subtle issues
- 💡Always add `LIMIT 100` while testing, then remove it for the full run
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