I need to investigate data quality issues more systematically. Let me examine the specific problems identified and look for additional issues. ```json { "action": "tool_call", "reasoning": "The evidence shows some quality issues (7 amount format issues, 119 n/a valuations, 26 n/a lead investors, 1 industry spelling variant, 10 duplicate companies). I need to examine the actual problematic values to understand the nature of these issues - what makes an amount format problematic, what the industry spelling variant is, and what the duplicate companies look like.", "tool": "query_sql", "args": { "sql": "SELECT Company, Amount, Valuation, Industry, \"Lead investors\", \"Date reported\" FROM raw.\"Largest US Venture Funding Deals Of 2023\" WHERE LENGTH(Amount) < 13 OR Amount NOT LIKE '$%' OR Valuation LIKE '%,%,%' OR Industry IN (SELECT Industry FROM raw.\"Largest US Venture Funding Deals Of 2023\" GROUP BY Industry HAVING COUNT(*) = 1 AND Industry LIKE '% %') ORDER BY Amount LIMIT 50", "purpose": "Examine rows with potential format issues in Amount field and identify the industry spelling variant" } } ```