I’ll walk you through a comprehensive solution that addresses all the validation challenges you’re facing.
Data Quality Assessment Enhancement:
First, create a pre-migration validation framework that mirrors Arena’s validation rules. Build SQL queries against your staging tables that check:
- Tax ID format per country (use regex patterns from Arena’s validation library)
- Uniqueness constraints across all identifier fields
- Required field completeness for vendor_classification, payment_terms, and risk_category
- Referential integrity for any foreign key relationships
Run this assessment daily during your data preparation phase to catch drift.
Vendor Tax ID Validation Rules:
For the duplicate tax ID issue, implement this resolution strategy:
- Query your staging data to identify all records sharing tax IDs
- For legitimate parent-subsidiary relationships, append a suffix to create unique identifiers (e.g., 45-1234567-01, 45-1234567-02)
- Use Arena’s supplier hierarchy feature to link these entities post-migration
- For actual duplicates (data quality issues), merge records in staging before import
- Document the tax ID transformation mapping for audit purposes
For format validation, create a country-specific validation lookup table that applies the correct pattern before staging.
Staging Table Validation Process:
Implement a three-tier validation architecture:
- Tier 1: Structural validation (data types, field lengths, null checks)
- Tier 2: Business rule validation (tax ID format, classification values, status codes)
- Tier 3: Cross-reference validation (existing supplier checks, duplicate detection)
Create a validation_results table that logs each failure with: record_id, validation_tier, error_code, error_description, remediation_status. This gives you traceable error management.
Incremental Import Strategy:
Structure your import in dependency-aware batches:
- Batch 1: Independent supplier records (no hierarchy relationships)
- Batch 2: Parent suppliers in hierarchies
- Batch 3: Subsidiary suppliers with parent references
- Batch 4: Supplier contacts and auxiliary data
Use Arena’s import API with transaction control - commit only after each batch validates completely. Implement checkpoint restart capability so failed batches can resume without re-processing successful records.
Error Logging and Remediation Workflow:
Set up an automated remediation pipeline:
- Parse error logs from Arena’s import response
- Categorize errors: data_format, business_rule, system_constraint
- Route to appropriate remediation queues (automated fix vs. manual review)
- For automated fixes: apply transformation rules and re-submit
- For manual review: generate remediation worksheets with specific guidance
- Track remediation SLA and escalate blocked items
Create a remediation dashboard showing: total errors, error categories, resolution rate, blocking issues. This keeps stakeholders informed and helps prioritize data cleanup efforts.
Implement this framework and your 340 failed records should resolve systematically. The key is moving validation left in your pipeline - catch issues before they hit Arena’s import process. This approach reduced our migration error rate from 12% to under 2%.