McKinsey reports that inefficiencies in data migration cost enterprises 14% more than their planned spending, with 38% of companies experiencing migration delays of over a quarter.[i]
These issues often arise from data inconsistencies, field mismatches, API limitations, and permission errors, leading to incomplete records, failed imports, and operational slowdown.
To streamline high-volume data operations, Salesforce offers Data Loader, a powerful ETL (Extract, Transform, Load) tool that enables users to efficiently insert, update, delete, and export large datasets. With its capability to handle millions of records, it simplifies complex data migration processes. However, common errors such as:
- INVALID_FIELD_FOR_INSERT_UPDATE
- INVALID_CROSS_REFERENCE_KEY
- UNABLE_TO_LOCK_ROW
Moreover, disrupted workflows—often caused by incorrect mappings, validation rule conflicts, or automation-triggered failures.
By understanding these frequent pitfalls and applying targeted fixes, organizations can improve data accuracy, reduce downtime, and ensure smooth CRM integrations.
In this blog post, we’ll dive into the eight most common Salesforce Data Loader errors, their root causes, and the most effective solutions to keep your data migration processes running seamlessly.
What is Salesforce Data Loader?
If you’re managing high-volume data operations in Salesforce, understanding Salesforce Data Loader is essential. This client application allows you to insert, update, delete, and export large datasets seamlessly within Salesforce. Whether you’re migrating legacy records, performing bulk updates, or backing up critical CRM data, Data Loader streamlines the process—handling anywhere from 50,000 to 5 million records per operation.
Unlike native tools like Salesforce Data Import Wizard, which supports smaller imports, Data Loader offers advanced functionality, including support for custom objects, scheduled data loads, and automation through command-line execution (Windows only). It processes CSV files for imports and can export data in the same format, ensuring compatibility across different systems.
Salesforce Data Loader is available for both Windows and macOS, and you can choose between an interactive UI or a command-line interface (CLI). The UI-based approach is ideal for one-time or ad-hoc imports, while the CLI option is preferred for automation, integrations, and scheduled jobs.
Top 5 Salesforce Data Loading Tools
1. Salesforce Data Import Wizard
- Best for: Small-scale data imports (up to 50,000 records)
- Key Features: Built into Salesforce, supports standard and custom objects, simple UI-based interface
- Limitations: Lacks automation, CLI support, and advanced scheduling
2. Salesforce Data Loader
- Best for: Bulk data processing (50,000–5 million records)
- Key Features: Supports standard/custom objects, CLI automation, scheduled imports/exports
- Limitations: Requires installation, does not support cloud storage integration
3. Dataloader.io
- Best for: Cloud-based, API-driven data operations
- Key Features: 100% web-based (no installation required), supports integrations with Box, Dropbox, FTP, and SFTP
- Limitations: Limited free-tier capabilities, relies on API-only access
4. Jitterbit Data Loader
- Best for: Enhanced automation and integration
- Key Features: Drag-and-drop mapping, scheduled automation, and integration with Jitterbit’s Harmony Cloud platform
- Limitations: More complex setup compared to standard Salesforce Data Loader
5. XL Connector (Formerly Enabler4Excel)
- Best for: Excel-based data operations
- Key Features: Allows users to fetch Salesforce data directly into Excel, manipulate it, and push updates back to Salesforce
- Limitations: Requires Excel knowledge, dependent on CSV-based operations
Choosing the Right Data Loader Tool
If you need a native, high-volume, automation-friendly tool, Salesforce Data Loader is your best bet. However, if you’re looking for cloud-based flexibility, advanced integrations, or Excel-native workflows, exploring third-party solutions like Dataloader.io, Jitterbit, or XL Connector can provide additional functionality tailored to your needs.
Common Errors in Salesforce Data Loader and How to Identify & Fix Them
Salesforce Data Loader is a powerful tool for bulk data operations, but errors can disrupt the process. These errors often arise from field mismatches, data formatting issues, API limitations, and permission conflicts.
Identifying the signs of these errors early can help you avoid data inconsistencies and workflow disruptions.
Below, we break down the most common Data Loader errors, the symptoms you might face, and how to fix them.
1. INVALID_FIELD_FOR_INSERT_UPDATE
Symptoms:
- The Data Loader import fails without updating records.
- Error message: INVALID_FIELD_FOR_INSERT_UPDATE: Field is not writable
- Certain fields (like formula fields) are not being updated.
Cause:
- The field you’re trying to update is read-only or restricted from updates.
- The field-level security (FLS) does not grant write permissions.
- The field is a formula field, which is system-generated and non-editable.
Solution:
- Check Field-Level Security (FLS) in Object Manager and ensure the user profile has edit access.
- Ensure that the field type supports updates—formula fields cannot be updated directly.
- Verify the API field names in the CSV file match exactly with the Salesforce schema.
2. REQUIRED_FIELD_MISSING
Symptoms:
- Some records fail to insert/update while others go through.
- Error message: REQUIRED_FIELD_MISSING: Required field is missing
- Data Loader imports stop at a certain percentage and return error logs.
Cause:
- A mandatory field in Salesforce is missing from the CSV file.
- Lookup or master-detail relationships require a related record that isn’t provided.
Solution:
- Check the object’s required fields in Object Manager.
- Ensure that all mandatory fields are populated in the CSV file before import.
- If the error involves a lookup field, verify that the related records already exist in Salesforce.
3. MALFORMED_ID
Symptoms:
- Error message: MALFORMED_ID: Invalid ID value
- Import fails when using Salesforce record IDs.
- Some ID values appear truncated or formatted incorrectly.
Cause:
- The Salesforce ID is not in the correct 15-digit or 18-digit format.
- The CSV file has modified IDs, possibly due to Excel auto-formatting.
- The import file references an incorrect object ID (e.g., Account ID instead of Contact ID).
Solution:
- Ensure all Salesforce IDs are in the correct 15-character (case-sensitive) or 18-character (case-insensitive) format.
- Open CSV files in Notepad or Google Sheets to prevent Excel from modifying IDs.
- If necessary, use Excel formulas like =UPPER(A1) to convert IDs to uppercase.
4. DUPLICATE_VALUE
Symptoms:
- Some records fail to import while others succeed.
- Error message: DUPLICATE_VALUE: Duplicate external ID value found
- New records fail to insert, especially when using Upsert.
Cause:
- The operation violates a unique field constraint (e.g., duplicate emails, usernames, external IDs).
- The Upsert operation attempts to insert duplicate records with the same External ID.
Solution:
- Check the unique field constraints in Object Manager.
- Ensure that External ID values in the import file are unique.
- Use Salesforce Duplicate Rules to identify and clean duplicate data before import.
5. INVALID_CROSS_REFERENCE_KEY
Symptoms:
- Lookup fields fail to populate correctly.
- Error message: INVALID_CROSS_REFERENCE_KEY: Invalid reference ID
- Import fails when referencing related records.
Cause:
- The referenced lookup value does not exist in Salesforce.
- The import file contains an incorrect external ID or Salesforce ID for a related object.
Solution:
- Ensure that all lookup values exist in Salesforce before running the import.
- If using External IDs, verify that they match the correct Salesforce record.
- Check for leading or trailing spaces in lookup values that might cause mismatches.
6. FIELD_INTEGRITY_EXCEPTION
Symptoms:
- Data Loader import fails with an error related to field values.
- Error message: FIELD_INTEGRITY_EXCEPTION: Invalid picklist value
- Picklist fields do not accept some imported values.
Cause:
- The provided value does not match the expected data type or picklist options.
- The import file contains values that are not in the allowed picklist options.
Solution:
- Ensure that the CSV file contains valid picklist values as defined in Salesforce.
- Check for spelling errors or case sensitivity mismatches.
- If importing data into a restricted picklist, either enable “Allow Unrestricted Picklist Values” in Setup or use valid options.
7. UNABLE_TO_LOCK_ROW
Symptoms:
- Bulk imports fail intermittently.
- Error message: UNABLE_TO_LOCK_ROW: Record currently locked by another process
- Updates are unsuccessful due to record locks.
Cause:
- A record is being updated simultaneously by another process (e.g., workflow, trigger, or another Data Loader operation).
- Salesforce is enforcing record locking to prevent conflicts.
Solution:
- Retry the import after a short delay.
- If processing large batches, enable Batch Mode in Data Loader to reduce conflicts.
- Check background processes (e.g., workflows, triggers, or Apex jobs) that might be locking records.
8. STORAGE_LIMIT_EXCEEDED
Symptoms:
- New records fail to import, and existing data operations halt.
- Error message: STORAGE_LIMIT_EXCEEDED: Data storage is full
- Salesforce reports that data storage capacity has been reached.
Cause:
- The Salesforce org has exceeded its allocated storage limit.
- Large data imports are consuming storage capacity.
Solution:
- Check Storage Usage in Salesforce (Setup → Data Storage).
- Delete old or unnecessary records (e.g., outdated leads, archived cases).
- Purchase additional storage if needed.
Final Thoughts
By proactively identifying these common Salesforce Data Loader errors, you can prevent failed imports, reduce manual troubleshooting, and improve data accuracy. A well-optimized Data Loader process ensures seamless data migration, automation, and bulk processing—helping you maintain clean, reliable data in Salesforce.
Statistical References
[i]Mckinsey