Cost Optimization Guide

altimate is your cost advocate. Here's how to use it to cut warehouse spend.

Step 1: Find where money is going

You: What's driving our Snowflake costs?

> finops_analyze_credits prod-snowflake --days 30
> finops_expensive_queries prod-snowflake --days 30 --limit 20

This gives you: - Credit breakdown by warehouse, user, and time - Top 20 most expensive queries with anti-pattern flags - Trend data (are costs increasing?)

Step 2: Fix the worst offenders

For each expensive query, the agent automatically runs sql_analyze to find anti-patterns:

SELECT * → explicit columns

Before: 89.3 credits/week

SELECT * FROM events e JOIN users u ON e.user_id = u.id

After: ~25 credits/week (72% savings)

SELECT e.event_id, e.event_type, e.created_at, u.name, u.email
FROM events e
JOIN users u ON e.user_id = u.id

Missing date filter on partitioned tables

Before: 45.1 credits (full table scan)

SELECT DISTINCT customer_id FROM orders WHERE status = 'active'

After: ~2.3 credits (95% savings)

SELECT DISTINCT customer_id
FROM orders
WHERE status = 'active'
  AND order_date >= DATEADD(day, -90, CURRENT_DATE())

Non-sargable predicates

Before: Scans entire column, can't use clustering

WHERE YEAR(order_date) = 2026

After: Enables partition pruning

WHERE order_date >= '2026-01-01' AND order_date < '2027-01-01'

Step 3: Right-size warehouses

You: Are our warehouses the right size?

> finops_warehouse_advice prod-snowflake --days 14

Common findings: - Over-provisioned warehouses. Utilization below 30% means you're paying for idle compute. - Missing auto-suspend. Warehouses running 24/7 when only used during business hours. - Wrong size for workload. Small queries on XL warehouses waste credits.

Step 4: Clean up unused resources

You: What tables and warehouses are unused?

> finops_unused_resources prod-snowflake --days 30

This finds: - Tables with no reads in 30+ days (costing storage) - Warehouses with no queries in 7+ days - Temporary tables from old migrations

Quick wins checklist

Action	Typical savings	Effort
Replace SELECT * with explicit columns	50-80% per query	Low
Add date filters to large table scans	80-95% per query	Low
Fix non-sargable WHERE clauses	30-60% per query	Low
Downsize over-provisioned warehouses	30-50% monthly	Medium
Enable auto-suspend (1 min)	10-20% monthly	Low
Drop unused tables	Storage savings	Low
Materialized views for repeated queries	90%+ per query	Medium
Incremental models instead of full refresh	50-90% per run	Medium