| name | data-validation-setup |
| description | One-time infrastructure setup for cloud data validation — verify the orchestrator service is ready after the shared infrastructure step. |
| parent_skill | migration |
| license | Proprietary. See License-Skills for complete terms |
Cloud Data Validation Setup
One-time infrastructure setup for validating migrated data between a source database and Snowflake using the Cloud Data Validation feature via the scai CLI.
Supported sources: SQL Server, Redshift, Oracle, Teradata, PostgreSQL
Supported target: Snowflake
Prerequisite
Load ../../data-infrastructure/SKILL.md first. It handles shared prerequisites, compute pool registration, and worker config (source host/port/credentials, source database, source schema). Return here after it completes.
Validation additionally requires that target tables are already deployed to Snowflake (run data migration first).
Step 1: Verify Orchestrator Service
After the shared infrastructure step has registered the compute pool, confirm the orchestrator service started:
SELECT SYSTEM$GET_SERVICE_STATUS('SNOWCONVERT_AI.DATA_MIGRATION.DATA_MIGRATION_SERVICE');
If it returns [] (suspended/not started), resume it manually:
ALTER SERVICE SNOWCONVERT_AI.DATA_MIGRATION.DATA_MIGRATION_SERVICE RESUME;
Wait 30-60s and re-check until status shows READY.
This completes infrastructure setup. The actual validation is started later by the validate-objects skill via:
progress_setup(mode="data_validation") — choose full vs incremental (+ sync strategy).validate_data(mode="setup", where=..., validation_type=..., sync_strategy=...) — generates artifacts/data_validation/workflows/<hash>.yaml and patches known toggles / sync strategy.data_infrastructure(mode="up") — bring the shared orchestrator + worker up once (if not already up for this session).- Agent edits (e.g.
watermarkColumn, partition columns) then validate_data(mode="run", workflow_path=...) — pure dispatch (scai data validate create-workflow) against the already-running infrastructure.
Do not run scai data validate create-workflow directly — use validate_data for dispatch and data_infrastructure for the orchestrator/worker lifecycle. Do not write ad-hoc comparison scripts — use the validation workflow YAML and validate_data instead.
When editing validation workflows, load Workflow Config Reference for camelCase field names and common edit scenarios (including excluding drift-prone timestamp columns from row compare before validate_data(mode="run")). For task-level debugging, see Task model reference.
Checklist
Shared infrastructure checklist is owned by ../../data-infrastructure/SKILL.md. Validation-specific items:
- [ ] Compute pool passed to data_infrastructure(mode="up", compute_pool=...) — SPCS only
- [ ] Worker config has no remaining <placeholder> values — unless pure Iceberg
- [ ] Level 1 scai data doctor — no Fail checks (see data-infrastructure skill)
- [ ] Data Validation Service running (READY)
Return control to the parent skill.
Reference
