I need to count distinct values for all categorical columns across the dataset. From the evidence I already have, I can see the distinct counts for each table's columns. Let me compile this information systematically. From the inspect_columns results I already obtained: **b2b_sales_funnel_pipeline:** - sales_agent: ~26 distinct - product: ~7 distinct - account: ~89 distinct - deal_stage: ~4 distinct **accounts:** - account: ~89 distinct - sector: ~11 distinct - office_location: ~13 distinct - subsidiary_of: ~9 distinct **sales_teams:** - sales_agent: ~32 distinct - manager: ~6 distinct - regional_office: ~3 distinct **products:** - product: ~7 distinct - series: ~3 distinct However, I notice the metadata shows "~" (approximate) counts. Let me get exact counts by querying each table directly to provide precise numbers. ```json { "action": "tool_call", "reasoning": "The inspect_columns results show approximate distinct counts (~). I need exact counts for all categorical columns. I'll write a single comprehensive query that counts distinct values for all categorical columns across all tables using UNION ALL to combine results.", "tool": "query_sql", "args": { "sql": "SELECT 'b2b_sales_funnel_pipeline' AS table_name, 'sales_agent' AS column_name, COUNT(DISTINCT sales_agent) AS distinct_count FROM raw.b2b_sales_funnel_pipeline UNION ALL SELECT 'b2b_sales_funnel_pipeline', 'product', COUNT(DISTINCT product) FROM raw.b2b_sales_funnel_pipeline UNION ALL SELECT 'b2b_sales_funnel_pipeline', 'account', COUNT(DISTINCT account) FROM raw.b2b_sales_funnel_pipeline UNION ALL SELECT 'b2b_sales_funnel_pipeline', 'deal_stage', COUNT(DISTINCT deal_stage) FROM raw.b2b_sales_funnel_pipeline UNION ALL SELECT 'accounts', 'account', COUNT(DISTINCT account) FROM raw.accounts UNION ALL SELECT 'accounts', 'sector', COUNT(DISTINCT sector) FROM raw.accounts UNION ALL SELECT 'accounts', 'office_location', COUNT(DISTINCT office_location) FROM raw.accounts UNION ALL SELECT 'accounts', 'subsidiary_of', COUNT(DISTINCT subsidiary_of) FROM raw.accounts UNION ALL SELECT 'sales_teams', 'sales_agent', COUNT(DISTINCT sales_agent) FROM raw.sales_teams UNION ALL SELECT 'sales_teams', 'manager', COUNT(DISTINCT manager) FROM raw.sales_teams UNION ALL SELECT 'sales_teams', 'regional_office', COUNT(DISTINCT regional_office) FROM raw.sales_teams UNION ALL SELECT 'products', 'product', COUNT(DISTINCT product) FROM raw.products UNION ALL SELECT 'products', 'series', COUNT(DISTINCT series) FROM raw.products ORDER BY table_name, column_name", "purpose": "Get exact distinct counts for all categorical columns across all tables in the dataset" } } ```