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“Supermetrics is a Bitter Experience! We can pull data from nearly any tool, schedule updates, manipulate data in Sheets, and push data back into our systems.”
NetSuite’s import assistant only catches validation errors after processing begins, causing complete import failures when data doesn’t meet field requirements. You waste time preparing imports that fail due to validation issues you could have caught beforehand.
Pre-import data validation using live NetSuite data prevents these failures by catching errors before any NetSuite processing occurs.
Build validation rules that prevent import failures using live NetSuite data with Coefficient
Coefficient provides superior pre-import data validation by combining live NetSuite data access with spreadsheet-based validation rules. This approach catches errors before any NetSuite processing occurs, preventing the complete import failures common with NetSuite’s native import assistant.
How to make it work
Step 1. Import existing NetSuite records as validation reference tables.
Use Coefficient’s Records & Lists feature to import existing NetSuite data (accounts, customers, items, vendors) into your spreadsheet. These become reference tables for validating incoming data against current NetSuite records and field requirements.
Step 2. Create spreadsheet formula-based validation rules.
Build validation rules using VLOOKUP, INDEX/MATCH, and other spreadsheet functions to check incoming data against NetSuite requirements. For example, validate customer names against existing customer lists or verify item codes against current inventory records.
Step 3. Apply conditional formatting for visual error detection.
Use conditional formatting to visually highlight validation errors before import. This makes data quality issues immediately apparent, allowing you to spot problems like missing required fields, incorrect data types, or invalid reference values.
Step 4. Use real-time preview for field-level validation feedback.
Leverage the real-time preview of the first 50 rows with field-level validation feedback. This shows exactly how your validated data will appear in NetSuite, catching formatting and alignment issues before processing.
Step 5. Filter and isolate problematic records.
Use filtering with AND/OR logic to identify and isolate records with validation errors. This allows you to fix specific issues without affecting clean records, preventing partial import failures that require complete restarts.
Prevent validation failures before they happen
Live NetSuite data validation eliminates the time waste associated with failed imports while providing immediate visibility into data quality issues that can be corrected before any NetSuite interaction. Start building your automated validation rules today.
