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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.”
Data validation is critical for successful NetSuite imports, but manual validation is time-consuming and error-prone. You can implement comprehensive validation rules that automatically apply to refreshed data and catch errors before they reach NetSuite.
Here’s how to set up automated validation workflows that transform one-time CSV validation into reusable, automated processes.
Build automated validation workflows with live data using Coefficient
Coefficient provides superior validation capabilities compared to traditional CSV preparation by working within spreadsheets with live data connections. You can implement comprehensive validation rules that automatically apply to refreshed data, catching errors before they impact NetSuite .
The platform enables spreadsheet-based validation rules that leverage Excel or Google Sheets’ native validation features on live imported data. You can filter data during import using AND/OR logic to exclude invalid records, and the real-time preview shows the first 50 rows for immediate identification of data quality issues.
How to make it work
Step 1. Import data with built-in filtering.
Use Coefficient’s Records & Lists import method with filtering capabilities to exclude invalid records before they reach your spreadsheet. Apply AND/OR logic filters for Date, Number, Text, and Boolean fields to ensure only clean data enters your validation workflow.
Step 2. Set up spreadsheet validation rules.
Apply Excel or Google Sheets’ native validation features to your imported data columns. Create data type checks, value ranges, required field validations, and custom field constraints that align with NetSuite ‘s requirements.
Step 3. Create visual validation dashboards.
Use conditional formatting to highlight validation failures visually and create validation summary dashboards using spreadsheet formulas. This provides immediate feedback on data quality issues across your entire dataset.
Step 4. Implement cross-reference validation.
Use SuiteQL queries to validate against existing NetSuite data, checking for duplicate records or valid customer IDs. Import NetSuite lists (customers, items, etc.) to validate foreign key relationships and ensure data integrity.
Step 5. Schedule automated validation refreshes.
Set up scheduled refreshes that maintain validation rules on new data automatically. This transforms one-time CSV validation into a reusable, automated process that catches errors consistently.
Transform validation from reactive to proactive
Automated validation workflows catch errors before they impact NetSuite, significantly reducing import failures and data quality issues. You get reusable validation processes that scale with your data volume and complexity. Start building reliable validation workflows today.
