All examples for Data Quality Validator

Sales Data with Revenue Reporting Issues

Validates sales transaction data containing critical issues including negative amounts, duplicate order IDs, missing values, and invalid email formats. Demonstrates severity classification, revenue impact quantification, and prioritized remediation recommendations for business reporting scenarios.

Input

What you provide to the skill

Validate sales data at /tmp/test1_sales.csv - checking for revenue reporting issues

Output

What the skill generates for you

Data Quality Validation Complete ✅

I’ve executed the Data Quality Validator skill on your sales data at /tmp/test1_sales.csv. Here’s what I found:

Overall Quality Score: 43/100 (POOR - Significant Issues) 🔴

Your sales data has critical revenue reporting issues that must be fixed before use:

🔴 CRITICAL ISSUES (Must Fix)

1. Negative Revenue Value

  • Row 7: ORD-008 shows -$50.00
  • This will make your revenue calculations incorrect
  • Action: Investigate if this is a refund/return → move to separate table

2. Duplicate Order ID

  • Rows 9-10: ORD-010 appears twice (identical records)
  • Impact: $249.95 revenue overcount (double-counted)
  • Action: Remove duplicate or split into order_lines table

🟠 HIGH PRIORITY ISSUES

3. Missing customer_email (Row 8, ORD-009) - 8.3% missing
4. Missing quantity (Row 7, ORD-007) - 8.3% missing
5. Invalid email format (Row 5: “invalid-email”)

💰 Revenue Impact Summary

  • Current total (with issues): $834.78
  • Corrected total: $584.83
  • Overcount: $249.95 due to duplicate
  • Negative amount needing investigation: -$50.00

✅ Recommended Actions (Priority Order)

  1. Fix duplicate ORD-010 → Corrects $249.95 overcount
  2. Investigate negative $50 amount → Prevents revenue undercount
  3. Backfill missing emails and quantities → Enables complete analysis
  4. Fix invalid email formats → Ensures customer contact ability

After fixing these issues, your quality score should improve from 43/100 to 85+/100 (audit-ready).

Would you like me to:

  • Export a detailed issue tracking CSV?
  • Help create SQL queries to find similar issues in your database?
  • Re-validate the data after you make corrections?
View all examples for Data Quality Validator

About This Skill

Validate CSV and Excel files before analysis. Detects missing values, duplicates, outliers, and format errors. Generates quality scores, severity-classified issues, and actionable remediation recommendations.

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