I need to identify the main categorical columns in this dataset and find their most common values with frequencies. Let me start by understanding what categorical columns exist. ```json { "action": "tool_call", "reasoning": "The previous query returned 0 rows, which suggests it may have been looking for something specific that didn't exist. I need to identify the main categorical columns across all tables. I'll query the column metadata to find columns with categorical/text types and reasonable cardinality (not too many distinct values to be meaningful categories).", "tool": "query_sql", "args": { "sql": "SELECT table_name, column_name, phys_type, semantic_role, rough_kind, distinct_count, null_count FROM analytics.column_overview WHERE rough_kind IN ('categorical', 'text', 'identifier') AND distinct_count > 1 AND distinct_count < 1000 ORDER BY distinct_count DESC LIMIT 30", "purpose": "Identify main categorical columns with reasonable cardinality for value frequency analysis" } } ```