I need to compute distribution statistics (min, max, mean, median, spread) for all numeric columns across all tables in this dataset. The evidence so far shows a sample of numeric columns from various tables, but I need comprehensive statistics across the entire dataset. Let me write a single SQL query that profiles all numeric columns at once, computing min, max, mean, median, and standard deviation (as a measure of spread). ```json { "action": "tool_call", "reasoning": "The evidence shows numeric columns exist across many tables (scores and plays tables). I need to compute distribution statistics for ALL numeric columns in the dataset. I'll query the analytics.column_overview metadata which already contains min_value, max_value, and avg_value for numeric columns, then supplement with a query for median and stddev where needed. First, let me get the complete picture from column_overview.", "tool": "query_sql", "args": { "sql": "SELECT table_name, column_name, phys_type, min_value, max_value, avg_value, null_count, distinct_count FROM analytics.column_overview WHERE phys_type IN ('BIGINT', 'DOUBLE', 'DECIMAL', 'INTEGER', 'FLOAT') ORDER BY table_name, column_name", "purpose": "Get min, max, mean for all numeric columns from metadata to understand the full distribution landscape", "source": "raw" } } ```