Data Migration Planner
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:
- Maps source → target schemas with field-level transformation rules
- Generates an ETL pipeline plan with staging, transform, and load phases
- Creates validation queries (row counts, checksum, referential integrity)
- Builds a rollback plan with point-of-no-return criteria
- 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:
- Executive summary (what, why, when, risk level)
- Schema mapping tables
- ETL pipeline specification
- Validation test suite
- Cutover runbook with rollback
- 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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