---
title: "Snowflake Data Source Template"
slug: "snowflake-data-source-template"
updated: 2026-04-08T18:48:56Z
published: 2026-04-08T18:48:56Z
canonical: "docs.validatar.com/snowflake-data-source-template"
---

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

# Snowflake Data Source Template

## Overview

The Snowflake data source template is a built-in SQL template designed for Snowflake cloud data warehouse connections. It ships with Validatar and provides complete metadata ingestion, data type mappings, profiling definitions, and macros optimized for Snowflake's SQL dialect and system views.

**Platform:** Snowflake Cloud Data Warehouse **Connection Category:** Database **Template Category:** Built-in

## What's Included

### Connection Configuration

- Supports Snowflake native connections
- Identifier delimiters: `"` / `"`
- Compatible with Snowflake's native pushdown execution engine

### Data Type Mappings

Includes mappings for all standard Snowflake data types:

- String types: `VARCHAR`, `STRING`, `TEXT`, `CHAR`
- Numeric types: `NUMBER`, `INTEGER`, `BIGINT`, `FLOAT`, `DOUBLE`
- Date/time types: `DATE`, `TIMESTAMP_NTZ`, `TIMESTAMP_LTZ`, `TIMESTAMP_TZ`, `TIME`
- Boolean: `BOOLEAN`
- Semi-structured: `VARIANT`, `OBJECT`, `ARRAY`
- Binary: `BINARY`, `VARBINARY`

### Default Parameters

### Execution Scripts

Recommended pre-execution scripts for Snowflake sessions:

```
ALTER SESSION SET TIMEZONE = 'UTC';
ALTER SESSION SET QUERY_TAG = 'validatar';
```

## Metadata Ingestion

### Schema Level

Queries `INFORMATION_SCHEMA.SCHEMATA` to discover all schemas, excluding `INFORMATION_SCHEMA`.

### Table Level

Queries `INFORMATION_SCHEMA.TABLES` to discover tables and views with schema, name, and type.

### Column Level

Queries `INFORMATION_SCHEMA.COLUMNS` to discover columns with data types, ordinal position, and nullability.

> **Note:** Snowflake's `INFORMATION_SCHEMA` queries operate within the context of the current database. Ensure the connection's database is set correctly.

## Profiling

Includes the standard set of ~40 profile definitions. Snowflake-specific considerations:

- Profiling functions use Snowflake SQL syntax
- `APPROX_PERCENTILE` can be used for approximate median calculations on large tables
- Semi-structured data types (`VARIANT`, `OBJECT`, `ARRAY`) have limited profiling support — basic profiles like `null_count` apply, but statistical profiles do not

## Macros

Built-in macros include standard patterns for:

- Row count checks
- Null percentage analysis
- Duplicate detection
- Value distribution queries

## Installation

The Snowflake template ships with Validatar — no import required. To verify it's available:

1. Navigate to **Settings > Data Source Templates**
2. Look for "Snowflake" in the template list
3. Ensure it is in **Active** status

## Configuration

After confirming the template is available:

1. Create a new data source or edit an existing one
2. Configure the connection with Snowflake connection type
3. Select the Snowflake template
4. Set the server name, database, warehouse, and credentials on the connection
5. Optionally customize pre-execution scripts for your specific role and warehouse

## Customization

Common customizations:

- **Schema filters** — Modify the schema ingestion script to include or exclude specific schemas
- **Custom macros** — Add macros for Snowflake-specific patterns (e.g., querying `ACCOUNT_USAGE` views, working with `VARIANT` data)
- **Profile definitions** — Add profiles that leverage Snowflake-specific functions
- **Execution scripts** — Set the appropriate role, warehouse, and session parameters for your environment

## Related Articles

- [What Is a Data Source Template?](/docs/what-is-a-data-source-template-overview)
- [Metadata Ingestion Scripts — SQL Templates](/docs/metadata-ingestion-scripts-sql-templates)
- [Profiling Configuration — SQL Templates](/docs/profiling-configuration-sql-templates)