Infor LN Data Migration Tools and Techniques
Data migration into Infor LN is a critical path activity in every implementation and upgrade project. LN's data model is complex—hundreds of interrelated tables with referential integrity constraints, mandatory field validations, and business rule enforcement. Loading data that violates any of these constraints causes cascading failures. This guide covers the tools, techniques, and methodologies that ensure successful data migration into LN environments.
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
Planning an LN data migration? Our migration specialists have loaded data into 80+ LN environments.
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