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