> ## Documentation Index
> Fetch the complete documentation index at: https://docs.asteragents.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Snowflake SQL Tool

> Execute SQL queries on your Snowflake data warehouse with enterprise-grade performance

## What it does

The Snowflake SQL tool executes SQL queries directly on your Snowflake data warehouse. Perfect for data analysis, reporting, business intelligence, and accessing large-scale datasets with Snowflake's cloud performance.

<Note>
  **Requires Snowflake Integration**: You need to set up a [Snowflake integration](/integrations/snowflake) before agents can use this tool.
</Note>

## Key features

* Execute any SQL query on Snowflake warehouses
* Automatic warehouse management and suspension
* Enterprise-grade security and performance
* Support for complex analytical queries
* Clean, structured result formatting

## Parameters

| Parameter | Type   | Required | Description                           |
| --------- | ------ | -------- | ------------------------------------- |
| `query`   | string | Yes      | The SQL query to execute on Snowflake |

## Common use cases

### Data analysis and reporting

```sql theme={null}
SELECT 
  DATE_TRUNC('month', order_date) as month,
  SUM(revenue) as total_revenue,
  COUNT(DISTINCT customer_id) as unique_customers
FROM sales_data 
WHERE order_date >= '2024-01-01'
GROUP BY month
ORDER BY month DESC;
```

Analyze sales trends and customer metrics.

### Customer segmentation

```sql theme={null}
SELECT 
  customer_segment,
  AVG(lifetime_value) as avg_ltv,
  COUNT(*) as customer_count
FROM customer_analytics
WHERE last_purchase_date >= DATEADD(month, -6, CURRENT_DATE())
GROUP BY customer_segment
ORDER BY avg_ltv DESC;
```

Segment customers based on behavior and value.

### Performance monitoring

```sql theme={null}
SELECT 
  warehouse_name,
  AVG(execution_time) as avg_execution_time,
  SUM(credits_used) as total_credits
FROM query_history
WHERE start_time >= DATEADD(day, -7, CURRENT_DATE())
GROUP BY warehouse_name
ORDER BY total_credits DESC;
```

Monitor warehouse performance and costs.

### Data quality checks

```sql theme={null}
SELECT 
  table_name,
  COUNT(*) as row_count,
  COUNT(DISTINCT primary_key) as unique_keys,
  SUM(CASE WHEN primary_key IS NULL THEN 1 ELSE 0 END) as null_keys
FROM information_schema.tables t
JOIN your_database.your_schema.your_table data ON 1=1
GROUP BY table_name;
```

Validate data quality and integrity.

### Complex analytics

```sql theme={null}
WITH monthly_cohorts AS (
  SELECT 
    customer_id,
    DATE_TRUNC('month', first_purchase_date) as cohort_month,
    DATE_TRUNC('month', order_date) as order_month
  FROM customer_orders
)
SELECT 
  cohort_month,
  COUNT(DISTINCT customer_id) as cohort_size,
  AVG(DATEDIFF(month, cohort_month, order_month)) as avg_months_active
FROM monthly_cohorts
GROUP BY cohort_month
ORDER BY cohort_month;
```

Perform advanced cohort analysis.

## Snowflake-specific features

* **Automatic scaling**: Warehouses scale based on query complexity
* **Zero-copy cloning**: Access cloned data without additional storage costs
* **Time travel**: Query historical data states
* **Secure data sharing**: Access shared datasets across organizations
* **Semi-structured data**: Query JSON, Parquet, and other formats natively

## Best practices

* Use appropriate warehouse sizes for your query complexity
* Leverage Snowflake's columnar storage with SELECT specific columns
* Use clustering keys for large tables to improve performance
* Take advantage of result caching for repeated queries
* Monitor credit usage and optimize expensive queries
* Use LIMIT clauses for exploratory queries

## Troubleshooting

**"Warehouse not found" or "Access denied"**

* Verify your Snowflake integration is properly configured
* Check that the specified warehouse exists and is accessible
* Ensure your user has the necessary permissions

**"SQL compilation error"**

* Validate your SQL syntax for Snowflake
* Check that table and column names exist
* Verify data types in your queries

**"Insufficient privileges"**

* Ensure your user has SELECT permissions on the tables
* Check that you have USAGE permissions on the database and schema
* Verify warehouse usage permissions

**"Query timeout"**

* Consider using a larger warehouse for complex queries
* Optimize your query with proper filtering and indexing
* Break large queries into smaller, more focused ones

## Related tools

* [Run Code](/tools/execute_python) - Analyze query results with code
* [Send Email](/tools/send_email) - Share reports and insights