Data Migration Fields
1. Description
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What it’s for: A narrative overview of this data migration — what data moves, from which source, to which target, and why.
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What to include:
- The source system and the target system.
- What data is being migrated and its significance to the business.
- Any key constraints or dependencies (e.g. “must complete before go-live”, “depends on DMG-2 completing first”).
- High-level transformation or cleansing required (detail goes in the Data Mapping tab).
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Example:
"All open and historical purchase orders from the legacy ERP are migrated to the new procurement platform. Open orders (status: pending or in-progress) are migrated as active records; historical orders (status: completed or cancelled) are migrated as read-only archive records. Supplier references must be remapped to the new supplier IDs assigned during the Supplier Master migration (DMG-1)."
2. Testing Strategy
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What it’s for: How this migration is tested before go-live.
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What to include:
- The approach: dry runs, parallel execution, subset testing, full rehearsal.
- Reconciliation methods: record counts, financial totals, checksum comparisons.
- Who performs the testing and who signs off on the results.
- Any automated validation queries or scripts.
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Example:
"Three dry runs to be performed in the pre-production environment. Each run includes a full record count reconciliation and a sample of 50 records verified manually by the Finance team. Final sign-off required from the Head of Finance before production migration is approved."
3. Pre-Migration Checks
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What it’s for: The go/no-go gate checks that must pass before the migration begins.
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What to include:
- Source data quality checks (completeness, referential integrity, no blocking errors).
- System readiness checks (source system available, target system ready to receive data, dependent migrations complete).
- Backup confirmation (source system backed up before migration starts).
- Access and permissions verified.
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Example:
- All suppliers in the source system have been matched to a target supplier ID (DMG-1 complete)
- Source ERP is in read-only mode and backup confirmed
- Target procurement platform is accessible and has passed smoke test
- Migration user account has confirmed write access to the target Data Set
4. Post-Migration Checks
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What it’s for: The validation steps run after the migration completes to confirm it succeeded.
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What to include:
- Record count comparison (source count = target count, or documented exceptions).
- Business reconciliation totals (e.g. total outstanding order value matches).
- Referential integrity checks in the target system.
- Sample record spot checks by the business.
- Any automated validation queries to run.
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Example:
- Total purchase order count in target = total in source (exceptions logged)
- Sum of open order values reconciles within £0 variance
- All purchase order line items have a valid product reference in target
- Finance team to verify 20 randomly selected orders against source records
5. Rollback Strategy
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What it’s for: What to do if the migration fails — how to restore the pre-migration state.
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What to include:
- The trigger conditions for invoking rollback (e.g. reconciliation fails, critical validation error).
- The rollback steps: which systems need to be reverted, in which order, and by whom.
- How long the rollback window is (the maximum time before rollback must be decided).
- Any data that cannot be rolled back and how that is handled.
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Example:
"If post-migration checks fail, invoke rollback within 2 hours of migration start. Rollback steps: (1) restore target database from pre-migration backup, (2) re-enable source ERP for read-write access, (3) notify stakeholders. Rollback decision authority: Head of IT and Head of Finance jointly. Note: any records manually created in the target during the migration window cannot be automatically rolled back and must be handled case-by-case."
Relationships
Data
| Relationship | What to link |
|---|---|
| Has Read Access to Data Set | Data Sets the migration reads from — the source data structures |
| Has Write Access to Data Set | Data Sets the migration writes to — the target data structures |
| Uses Business Information | Business Information items that this migration carries or transforms |
| Has Test Data | Test data sets used to validate this migration during dry runs or testing |
Technical Components
| Relationship | What to link |
|---|---|
| Uses API | APIs through which the migration is implemented (e.g. a target system import API) |
| Uses Stream | Message queues or event streams used by this migration |
| Uses Service | Backend services that participate in this migration |
| Uses Technology | Technologies used to implement this migration (e.g. ETL tool, migration script platform) |
Requirements Traceability
| Relationship | What to link |
|---|---|
| Supports Business Requirement | Business Requirements that this migration fulfils |
| Supports Non-Functional Requirement | NFRs that apply to this migration (e.g. performance, data retention) |
| Supports Transition Requirement | Transition Requirements that this migration is the response to |
Acceptance and Testing
| Relationship | What to link |
|---|---|
| Has Acceptance Criteria | Business-level criteria for confirming this migration has succeeded |
| Has Implementation Acceptance Criteria | Technical criteria for confirming the migration was implemented correctly |
RAID and Work
| Relationship | What to link |
|---|---|
| Has Risk | Risks associated with this migration (data quality risk, timing risk, rollback complexity) |
| Has Assumption | Assumptions made about this migration (e.g. assumed source data quality, assumed access) |
| Has Issue | Known issues affecting the definition or execution of this migration |
| Has FAQ | Frequently asked questions about this migration |
| Has Task | Tasks assigned to this migration (preparation, dry runs, sign-off activities) |
Reference
| Relationship | What to link |
|---|---|
| Implements Business Reference | Standards, policies, or regulatory documents governing this migration (e.g. data retention policy, GDPR requirements) |