I need to identify columns with missing values and calculate the percentage of missing data for each column in the dataset. Let me start by querying the column metadata to get null counts for all columns in the table. ```json { "action": "tool_call", "reasoning": "I'll query the analytics.column_overview metadata table to get null counts for all columns in raw.ittf_player_info. This will show me which columns have missing values and allow me to calculate the percentage missing.", "tool": "query_sql", "args": { "sql": "SELECT column_name, null_count, (SELECT row_count FROM analytics.table_overview WHERE table_name = 'raw.ittf_player_info') as total_rows, ROUND(100.0 * null_count / (SELECT row_count FROM analytics.table_overview WHERE table_name = 'raw.ittf_player_info'), 2) as pct_missing FROM analytics.column_overview WHERE table_name = 'raw.ittf_player_info' AND null_count > 0 ORDER BY pct_missing DESC", "purpose": "Find all columns with missing values and calculate the percentage missing for each", "source": "raw" } } ```