validate-objects

Validate data consistency between source systems and Snowflake post-migration.

1|1|Updated Apr 15, 2026

Search Tags:#database #validation #data integrity #migration #cloud #snowflake

Ready to run

npx skills add https://github.com/Snowflake-Labs/cortex-code-migrations --skill validate-objects

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: validate-objects
Source: https://github.com/Snowflake-Labs/cortex-code-migrations/tree/main/plugin/skills/migration/validate-objects
Command: npx skills add https://github.com/Snowflake-Labs/cortex-code-migrations --skill validate-objects

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Validates migrated data across source systems and Snowflake to ensure accuracy and consistency.

Core Features & Use Cases

Data Validation: Compares row counts, schema, and data metrics to verify migration success.
Use Case: When migrating a large database, confirm that tables in Snowflake match source data to prevent discrepancies.
Operational Scope: Can validate multiple tables in a batch, supporting cloud-based validation workflows within Snowflake environments.

Quick Start

Use the validate objects skill to check the consistency of your migrated tables in Snowflake against the source database.

Frequently Asked Questions about validate-objects

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I validate data consistency between a source database and Snowflake after migration?▼

To validate data consistency post-migration, you can compare row counts, schema structures, and data metrics between your source systems and Snowflake. This process verifies migration accuracy by confirming that tables match the original source data and preventing discrepancies.

What is the best way to verify row counts and schema matching in Snowflake?▼

The best way to verify row counts and schema matching is by running end-to-end validation workflows that compare these metrics directly against your source database. This approach confirms that your migrated tables in Snowflake accurately reflect the original source data structure.

Can I validate multiple database tables in a batch within Snowflake?▼

Yes, you can validate multiple tables in a batch within Snowflake environments. The validation workflow supports batch processing to streamline the verification of data accuracy and schema matching across numerous migrated tables simultaneously.

Do I need any specific dependencies to run cloud validation scripts for data integrity?▼

No specific external dependencies are required to run cloud validation scripts for data integrity. The process implements cloud validation APIs and scripts directly to streamline validation tasks within your existing Snowflake environment without additional setup.

When do I need to perform end-to-end data validation for a cloud migration?▼

You need to perform end-to-end data validation immediately after completing a cloud migration to Snowflake. This ensures that data accuracy, schema matching, and row count verification are maintained and that no discrepancies occurred during the database transfer.