I need to explore this dataset systematically to find surprising or counterintuitive patterns. Let me start by understanding the sales funnel dynamics and then look for anomalies. {"action": "tool_call", "reasoning": "First, I'll examine the deal stage distribution and conversion patterns to understand the funnel structure and identify any unusual patterns in how deals progress.", "tool": "query_sql", "args": {"sql": "SELECT deal_stage, COUNT(*) as deal_count, ROUND(AVG(close_value), 2) as avg_value, ROUND(SUM(close_value), 2) as total_value, ROUND(100.0 * COUNT(*) / SUM(COUNT(*)) OVER (), 1) as pct_of_deals FROM raw.b2b_sales_funnel_pipeline GROUP BY deal_stage ORDER BY deal_count DESC", "purpose": "Understand the distribution of deals across stages and their values to identify any counterintuitive patterns in the funnel", "source": "raw"}}