```json { "action": "tool_call", "reasoning": "I have overall statistics and some extreme values, but I need to check for specific data quality issues. Let me examine: 1) Whether there are any NULL values in key columns, 2) Whether there are any duplicate rows, and 3) Whether the measurements are consistent (no negative values, reasonable ranges for biological measurements). I'll write a comprehensive query to check for these issues.", "tool": "query_sql", "source": "raw", "purpose": "Check for NULL values, negative values, and duplicate rows to identify data quality issues", "sql": "WITH null_check AS (SELECT COUNT(*) FILTER (WHERE SepalLengthCm IS NULL) as sepal_length_nulls, COUNT(*) FILTER (WHERE SepalWidthCm IS NULL) as sepal_width_nulls, COUNT(*) FILTER (WHERE PetalLengthCm IS NULL) as petal_length_nulls, COUNT(*) FILTER (WHERE PetalWidthCm IS NULL) as petal_width_nulls, COUNT(*) FILTER (WHERE Species IS NULL) as species_nulls FROM raw.Iris), negative_check AS (SELECT COUNT(*) FILTER (WHERE SepalLengthCm < 0) as sepal_length_negative, COUNT(*) FILTER (WHERE SepalWidthCm < 0) as sepal_width_negative, COUNT(*) FILTER (WHERE PetalLengthCm < 0) as petal_length_negative, COUNT(*) FILTER (WHERE PetalWidthCm < 0) as petal_width_negative FROM raw.Iris), duplicate_check AS (SELECT COUNT(*) as duplicate_count FROM (SELECT SepalLengthCm, SepalWidthCm, PetalLengthCm, PetalWidthCm, Species, COUNT(*) as cnt FROM raw.Iris GROUP BY SepalLengthCm, SepalWidthCm, PetalLengthCm, PetalWidthCm, Species HAVING COUNT(*) > 1)) SELECT * FROM null_check, negative_check, duplicate_check" } ```