The "Select All" Disaster
In the old world of on-prem databases (Oracle, SQL Server), a bad SQL query was annoying. It made the dashboard load slowly. In the new world of Cloud Data Warehouses (Snowflake, BigQuery, Databricks), a bad SQL query is expensive.
We recently audited a client who couldn’t understand why their data bill doubled in one month. The culprit? A single dashboard. It was running a SELECT * query across a 10TB table every 15 minutes. That one query was burning $4,000/month in compute credits.
Your Data Warehouse is not a storage locker; it is a high-performance engine. And like a supercar, if you rev the engine unnecessarily, you burn fuel (money) fast.
Understanding the "Consumption Model"
Most don’t understand that they aren’t paying for “Data Storage” anymore (Storage is cheap). They are paying for Compute Time.
The Warehouse Size: A “4X-Large” warehouse costs 128 credits/hour. That’s roughly $400/hour.
The Duration: If you leave that warehouse running 24/7 because of a misconfigured “Auto-Suspend” setting, you are burning $10,000/day.
The Silent Killer (Idle Time)
The easiest win in Data FinOps is “Auto-Suspend.” Many tools default to suspending the warehouse after 10 or 15 minutes of inactivity. This is throwing money away. If a query takes 10 seconds to run, but the warehouse stays on for 10 minutes waiting for the next one, you are paying for 9 minutes and 50 seconds of “Air.” Best Practice: Set Auto-Suspend to 60 seconds for most workloads.
Who is burning your budget? Do you know your Top 10 most expensive queries? Audit your Data Warehouse usage.
Your Data Warehouse is not a storage locker; it is a high-performance race car engine. If you leave it idling in the driveway, you are still burning premium fuel. Read the full strategy + Take the assessment #Snowflake #BigQuery #DataEngineering #FinOps #SQL #AI
Hunting the "Table Scans"
The technical root cause of high costs is usually Full Table Scans. This happens when an analyst writes a query without a WHERE clause or a LIMIT. The database has to read every single row on the disk. The Fix:
Clustering/Partitioning: Organize data so the DB only reads what it needs.
Resource Monitors: Set a “hard limit” quota. If a warehouse hits 110% of its budget, kill it automatically.
Conclusion: Code is Cost In the cloud, SQL code is a financial transaction. Every time an engineer presses “Run,” they are spending company money. You need guardrails, not just guidelines.
Stop the Bleeding Audit your Warehouses, Queries, and RBAC roles.
Understanding that “Idle Time” is a silent killer is step one. Step two is identifying exactly which dashboards and analysts are leaving the engine running.
We use a proprietary Data Cost Framework at GYSP to help enterprises configure auto-suspend, identify expensive queries, and stop the bleeding.
Stop guessing about your data bill. Use the exact diagnostic tool we use with our enterprise clients to measure your warehouse efficiency.
👇 Take the Data Cost Assessment Below:
