Error handling is one of the most important aspects of maintaining a healthy data integration. Knowing when to let a transfer continue despite errors, and how to interpret and resolve data errors effectively, keeps your integrations running smoothly without letting problems go unnoticed.
This guide covers best practices for using Continue on Error, reading and understanding data error logs, and safely reprocessing records after fixing root causes in MyRapidi.
In the 7th Session of our Open Office Hours series, we cover Continue on Error and Data Errors in Rapidi.
Continue on Error & Data Errors
Quick Summary:
In this Open Office Hours session, we walk through how to use Continue on Error and how to work with data errors in MyRapidi to keep your integrations running reliably.
Topics covered include:
- Continue on Error functionality – When and why to enable this feature so transfers keep processing even when individual records fail
- Interpreting Data Errors – How to navigate and understand error logs in MyRapidi to quickly identify what went wrong
- Common error scenarios – Validation failures, missing required fields, duplicate keys, and other frequent issues
- Safe reprocessing – How to fix root causes and re-sync affected records without creating duplicates or data conflicts
We also share practical tips on monitoring strategies to prevent errors from accumulating unnoticed and maintaining overall integration health.
Watch the Replay of our seventh session: Continue on Error & Data Errors
Continue on Error & Data Errors in RAPIDI: Monitoring, Troubleshooting, and Recovery
When transferring data between systems, errors are inevitable. Records may fail validation, required fields may be missing, or duplicate keys may be encountered. The key is to handle these errors gracefully so that a single problematic record does not block the entire transfer. Rapidi's Continue on Error feature and data error management tools give you control over how errors are handled and resolved.
What is Continue on Error?
Continue on Error is a transfer setting in Rapidi that determines what happens when an individual record encounters an error during processing.
How it works
- When enabled, the transfer skips the failing record and continues processing the remaining records. The failed record is logged as a data error for later review.
- When disabled, the transfer stops entirely at the first error. No further records are processed until the issue is resolved.
When to enable Continue on Error
- High-volume transfers where one bad record should not block hundreds of valid ones
- Scheduled transfers that run overnight or unattended
- Initial data loads where some source data may be incomplete
- Integrations where business operations depend on timely data flow
When to keep it disabled
- Transfers where data integrity requires all-or-nothing processing
- Financial or compliance-sensitive data where partial transfers could cause issues
- During development and testing, when you want to catch every error immediately
Understanding Data Errors in MyRapidi
When Continue on Error is enabled and a record fails, it appears as a data error in MyRapidi. Data errors provide detailed information about what went wrong and which record was affected.
What a data error contains
- Record identifier – Which specific record failed (e.g., customer number, order ID)
- Error message – The error returned by the source or destination system
- Timestamp – When the error occurred
- Transfer context – Which transfer and run produced the error
Navigating the data error log
MyRapidi provides a dedicated view for data errors that lets you:
- Filter errors by transfer, date range, or error type
- Sort errors to prioritize the most recent or most frequent issues
- View the full error detail for each failed record
- Track whether errors have been addressed or are still outstanding
Common Error Scenarios
Understanding the most frequent error types helps you resolve them faster and prevent recurrence.
1) Validation failures
The destination system rejects a record because a field value does not meet its validation rules. Common causes include:
- Email fields with invalid formats
- Phone numbers that do not match expected patterns
- Numeric fields receiving text values
2) Missing required fields
A record is sent without a value that the destination system requires. This often happens when:
- Source records have optional fields that are mandatory in the destination
- Lookup formulas return blank values without a proper fallback
- New required fields are added to the destination system after the integration was set up
3) Duplicate key violations
The destination system already contains a record with the same unique identifier. This can occur when:
- Records are created manually in the destination before the integration syncs them
- A previous transfer was partially completed and is then re-run
- Link storage is out of sync with the actual destination records
4) Permission and access errors
The integration user does not have sufficient permissions to create or update records in a particular object or table. Check the integration user's role and permissions in the destination system.
Safe Reprocessing of Failed Records
Once you have identified and fixed the root cause of a data error, you need to reprocess the affected records. Rapidi provides mechanisms to do this safely.
Steps for safe reprocessing
- Identify the root cause – Review the error message and understand why the record failed
- Fix the issue – Correct the data in the source system, update the field mapping, or adjust destination settings
- Reprocess the record – Use MyRapidi's reprocessing feature to re-sync only the affected records
- Verify success – Check that the record now appears correctly in the destination and the data error is cleared
Avoiding common reprocessing mistakes
- Do not reprocess before fixing the root cause – the same error will recur
- Check link storage before reprocessing to avoid duplicate creation
- For bulk reprocessing, start with a small batch to verify the fix works
Monitoring Strategies
Proactive monitoring prevents data errors from accumulating and causing downstream issues.
Best practices for error monitoring
- Check the data error log regularly, ideally as part of a daily routine
- Set up notifications or schedule regular reviews of transfer health
- Track error trends over time – a sudden increase may indicate a system change
- Address errors promptly rather than letting them accumulate
- Use the MESSAGE formula in field mappings to log record identifiers for faster troubleshooting
Summary
Continue on Error and data error management are essential tools for maintaining reliable data integrations. Enable Continue on Error for high-volume and scheduled transfers to prevent single-record failures from blocking your data flow. Use MyRapidi's data error logs to identify, understand, and resolve issues efficiently. Always fix root causes before reprocessing, and establish monitoring routines to catch problems early.
What's Next
Stay tuned for the next session in our Open Office Hours series. Each week we cover a new topic to help you get the most out of your Rapidi integration.
Can't attend live? Register anyway, and we'll send you the recording and materials afterward.
Register for Session 8
Frequently Asked Questions
What does Continue on Error do in Rapidi?
Continue on Error is a transfer setting that tells Rapidi to keep processing remaining records when one record fails. Instead of stopping the entire transfer, the failing record is logged as a data error and the rest of the batch continues. This is especially useful for high-volume or scheduled transfers where you don't want a single bad record to block everything.
Should I always enable Continue on Error?
Not necessarily. For most production transfers, especially scheduled ones, enabling it makes sense so your integration keeps running. However, during development and testing, keeping it disabled helps you catch errors immediately. For compliance-sensitive transfers where partial data could cause problems, you may want to keep it off so issues are addressed before any data moves.
How do I find and view data errors in MyRapidi?
MyRapidi has a dedicated data error view where all failed records are listed. You can filter by transfer, date range, or error type. Each error entry shows the record that failed, the error message from the source or destination system, and the transfer run that produced it. This gives you the context needed to diagnose and fix the issue.
What are the most common causes of data errors?
The most frequent causes include validation failures (wrong data format), missing required fields (source has optional fields that are mandatory in the destination), duplicate key violations (record already exists), and permission errors (integration user lacks access). Understanding these patterns helps you set up preventive measures in your field mappings.
How do I safely reprocess failed records?
First, identify and fix the root cause of the error. Then use MyRapidi's reprocessing feature to re-sync only the affected records. Always verify that the fix works on a small batch before reprocessing in bulk. Check link storage to avoid creating duplicates, and confirm the records appear correctly in the destination after reprocessing.
