Migration Tools and Loading Methods
Infor LN provides several data loading mechanisms: the Data Migration Workbench for guided master data import, session-based data entry for transaction migration, BShell import scripts for custom load processes, and direct database loading for high-volume scenarios. Each method has trade-offs between speed, validation coverage, and complexity. The Data Migration Workbench validates data against LN business rules but is slower; direct loading is fast but bypasses validation.
- Use the Data Migration Workbench for master data: items, BOMs, customers, vendors, and chart of accounts
- Use session-based loading for open transactions that must pass full business logic validation
- Reserve direct database loading for high-volume historical data after thorough validation in staging tables
- Build BShell import scripts for data types not supported by the standard workbench with custom validation
Data Validation and Quality Assurance
Data validation occurs at three stages: pre-load validation in staging tables, load-time validation through LN business rules, and post-load verification comparing source counts and values to LN. Pre-load validation catches 80% of issues at a fraction of the cost, invalid codes, orphaned references, data type mismatches, and missing mandatory fields. Build validation rules based on LN's table definitions and constraint documentation.
- Build staging tables mirroring LN target table structures with identical data types and constraints
- Validate referential integrity in staging: every foreign key must have a corresponding master record
- Run record counts, value totals, and hash comparisons between source, staging, and LN after each load
- Create a data issue tracker capturing every validation failure with root cause and remediation status
Migration Methodology and Cutover Planning
Successful LN migrations follow an iterative methodology: analyze source data, design mapping rules, build transformation scripts, load to a sandbox, validate results, fix issues, and repeat until quality targets are met. Plan for 3-5 migration trial runs before the production cutover. The cutover itself should follow a detailed minute-by-minute runbook with go/no-go decision points, rollback procedures, and clear ownership for each step.
- Execute at least 3 full trial migrations measuring load times, error rates, and validation results each iteration
- Build a cutover runbook with exact timing, responsible parties, validation checkpoints, and rollback triggers
- Define go/no-go criteria for each cutover checkpoint: data quality thresholds, load time limits, and error budgets
- Plan the production cutover during a long weekend to allow buffer time for unexpected issues and validation
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