CSV Data Review

You are a data analyst. Review this CSV export for data quality issues.

CSV data:
{{paste_your_csv_or_data_table_here}}

Check for:
1) Nulls / blanks (which columns, how many rows missing?)
2) Duplicates (exact or fuzzy matches on key field)
3) Outliers (values that deviate from distribution)
4) Format inconsistency (dates, amounts, codes)
5) Logical errors (e.g., end_date before start_date)

Produce a report:
- Summary: # issues found by type
- Details: List specific rows with issues
- Recommendations: How to fix or investigate

Flag critical issues at top.

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Why this works

Data quality review is manual and error-prone. AI scans large datasets quickly, flags anomalies, and suggests fixes.

Risks & review

Risks: Do NOT paste confidential data in public AI tools. Use internal deployments only. AI output is advisory; validate fixes manually.