Data Migration Planner

Plans and documents detailed data migrations, including schema mapping, ETL pipeline design, validation tests, rollback strategies, and runbook creation.

Plan, execute, and validate data migrations between systems. Covers schema mapping, ETL pipeline design, rollback strategies, and post-migration validation.

What It Does

Given source and target system details, this skill:

1. Maps source → target schemas with field-level transformation rules
2. Generates an ETL pipeline plan with staging, transform, and load phases
3. Creates validation queries (row counts, checksum, referential integrity)
4. Builds a rollback plan with point-of-no-return criteria
5. Produces a migration runbook with go/no-go gates

Usage

Tell your agent:

• "Plan a migration from Salesforce to HubSpot CRM"
• "Create a data migration runbook for moving from MySQL to PostgreSQL"
• "Map our legacy ERP data to the new system schema"

Migration Framework

Phase 1: Discovery

• Inventory all source tables/objects and record counts
• Document data types, constraints, and relationships
• Identify data quality issues (nulls, duplicates, orphans)
• Map business rules that affect data interpretation

Phase 2: Schema Mapping

For each source entity, document:

Source Field	Type	Target Field	Type	Transform	Notes
(field)	(type)	(field)	(type)	(rule)	(edge cases)

Phase 3: ETL Pipeline

Extract → Stage (raw) → Clean → Transform → Validate → Load → Verify

• Extract: Full vs incremental, API vs direct DB, rate limits
• Stage: Raw landing zone, no transforms, audit trail
• Clean: Dedup, null handling, encoding fixes
• Transform: Type conversions, lookups, calculated fields
• Validate: Pre-load checks (counts, checksums, business rules)
• Load: Batch size, parallelism, error handling
• Verify: Post-load reconciliation

Phase 4: Validation

• Row count match (source vs target, per table)
• Checksum validation on key columns
• Referential integrity checks
• Business rule validation (e.g., all active accounts migrated)
• User acceptance sampling (random 5% manual review)

Phase 5: Cutover

• Go/no-go criteria checklist
• Point-of-no-return definition
• Rollback procedure and time estimate
• Communication plan (users, stakeholders)
• Parallel run period (if applicable)

Risk Factors

• Data volume: >10M rows = batch strategy required
• Downtime window: Zero-downtime needs CDC/dual-write
• Data quality: Garbage in = garbage out. Clean BEFORE migrating
• Dependencies: Other systems reading from source during migration
• Compliance: GDPR/HIPAA data handling during transit

Output Format

Deliver a migration runbook as structured markdown with:

1. Executive summary (what, why, when, risk level)
2. Schema mapping tables
3. ETL pipeline specification
4. Validation test suite
5. Cutover runbook with rollback
6. Timeline with milestones

Cost Estimation

Typical migration costs by complexity:

• Simple (1-5 tables, <1M rows): $5K-$15K or 1-2 weeks internal
• Medium (10-50 tables, 1-10M rows): $25K-$75K or 1-2 months
• Complex (50+ tables, 10M+ rows, multiple systems): $100K-$500K or 3-6 months

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