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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1---2name: afrexai-data-migration3description: Data Migration Planner4---5# Data Migration Planner67Plan, execute, and validate data migrations between systems. Covers schema mapping, ETL pipeline design, rollback strategies, and post-migration validation.89## What It Does1011Given source and target system details, this skill:121. Maps source → target schemas with field-level transformation rules132. Generates an ETL pipeline plan with staging, transform, and load phases143. Creates validation queries (row counts, checksum, referential integrity)154. Builds a rollback plan with point-of-no-return criteria165. Produces a migration runbook with go/no-go gates1718## Usage1920Tell your agent:21- "Plan a migration from Salesforce to HubSpot CRM"22- "Create a data migration runbook for moving from MySQL to PostgreSQL"23- "Map our legacy ERP data to the new system schema"2425## Migration Framework2627### Phase 1: Discovery28- Inventory all source tables/objects and record counts29- Document data types, constraints, and relationships30- Identify data quality issues (nulls, duplicates, orphans)31- Map business rules that affect data interpretation3233### Phase 2: Schema Mapping34For each source entity, document:35| Source Field | Type | Target Field | Type | Transform | Notes |36|---|---|---|---|---|---|37| (field) | (type) | (field) | (type) | (rule) | (edge cases) |3839### Phase 3: ETL Pipeline40```41Extract → Stage (raw) → Clean → Transform → Validate → Load → Verify42```43- **Extract**: Full vs incremental, API vs direct DB, rate limits44- **Stage**: Raw landing zone, no transforms, audit trail45- **Clean**: Dedup, null handling, encoding fixes46- **Transform**: Type conversions, lookups, calculated fields47- **Validate**: Pre-load checks (counts, checksums, business rules)48- **Load**: Batch size, parallelism, error handling49- **Verify**: Post-load reconciliation5051### Phase 4: Validation52- Row count match (source vs target, per table)53- Checksum validation on key columns54- Referential integrity checks55- Business rule validation (e.g., all active accounts migrated)56- User acceptance sampling (random 5% manual review)5758### Phase 5: Cutover59- Go/no-go criteria checklist60- Point-of-no-return definition61- Rollback procedure and time estimate62- Communication plan (users, stakeholders)63- Parallel run period (if applicable)6465## Risk Factors66- **Data volume**: >10M rows = batch strategy required67- **Downtime window**: Zero-downtime needs CDC/dual-write68- **Data quality**: Garbage in = garbage out. Clean BEFORE migrating69- **Dependencies**: Other systems reading from source during migration70- **Compliance**: GDPR/HIPAA data handling during transit7172## Output Format73Deliver a migration runbook as structured markdown with:741. Executive summary (what, why, when, risk level)752. Schema mapping tables763. ETL pipeline specification774. Validation test suite785. Cutover runbook with rollback796. Timeline with milestones8081## Cost Estimation82Typical migration costs by complexity:83- Simple (1-5 tables, <1M rows): $5K-$15K or 1-2 weeks internal84- Medium (10-50 tables, 1-10M rows): $25K-$75K or 1-2 months85- Complex (50+ tables, 10M+ rows, multiple systems): $100K-$500K or 3-6 months8687---8889**Built by [AfrexAI](https://afrexai-cto.github.io/context-packs/)** — AI Context Packs for business automation.9091Calculate your AI automation ROI: [Revenue Calculator](https://afrexai-cto.github.io/ai-revenue-calculator/)
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