For the complete documentation index, see llms.txt. This page is also available as Markdown.

Step 4: Running Checks and Reviewing Results

Once you have reviewed your scripts and are confident they are correct, it is time to execute them against the dataset.

Step 1: Run All Checks

Click Run All Checks to execute every validation script in the project. The platform runs all checks against your respondent data and returns results within seconds, regardless of dataset size.

Once the checks have run, the yellow dot next to each question would indicate that there are respondents flagged for the checks run for that question.

Step 2: View Flagged Respondents

For any check that failed, click the View button next to it. This takes you directly to the Respondents tab, automatically filtered to show only the respondents who failed that specific check. The columns are also filtered to display only the relevant variables, so you can immediately see the problematic data without sifting through the full dataset.

This makes it straightforward to understand exactly which respondents were flagged and why.

Step 3: Export the Validation Report

Once you have reviewed the results, click Export to download a comprehensive validation report.

The report is an Excel file that includes:

  • Summary sheet — Overall pass rate, total respondents, number of checks run, and counts of flagged respondents.

  • Detailed findings — Each failed check listed with the question text, the validation condition, the number of respondents who failed, and their respondent IDs.

  • Per-respondent breakdown — Grouped by question and check, showing exactly which respondents failed and what checks.

This report can be shared with your programming team, QA team, or clients to communicate data quality findings and drive corrective action.

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