Dealing with Data Import/Export Errors

Data import/export errors can disrupt workflows, but they are often straightforward to fix. Here’s how to handle common data issues within our platform.

Common Import Errors

1. Incorrect File Format: Ensure the data file you’re importing is in the correct format (e.g., CSV, JSON). Our platform supports specific formats; refer to our documentation for details.
2. Data Validation Errors: Check for missing fields, incorrect data types, or formatting errors in your data. Correct these issues before re-importing.

Common Export Errors

1. Incomplete Data Export: Ensure that all relevant filters and parameters are correctly set before exporting data. This will ensure you receive a complete dataset.
2. File Size Limits: Large data exports may exceed file size limits. Consider exporting data in smaller segments or using a different format.

Best Practices for Data Handling

• Data Backup: Always keep a backup of your original data before importing or exporting. This ensures you have a safe copy in case of errors.
• Test with Sample Data: Before importing a large dataset, test the process with a smaller sample to identify potential issues.
• Use Data Mapping: Utilize our platform’s data mapping features to match your data fields correctly during import.

Resolving Errors

• Error Messages: Pay attention to any error messages during the import/export process. These messages often provide specific information about what went wrong and how to fix it.
• Check Documentation: Our platform’s documentation includes detailed instructions and troubleshooting tips for handling data.

If you encounter persistent data import/export issues, contact our support team for expert assistance.