I'll systematically check for data quality issues across the key columns in this ITTF player dataset. {"action": "tool_call", "reasoning": "Start by examining Birth year for outliers and impossible values. The range shows 0..2014, which includes suspicious values (year 0 is impossible, and very old birth years would be implausible for active players). I'll get the distribution to identify problematic ranges.", "tool": "query_sql", "args": {"sql": "SELECT Birth_year, COUNT(*) as player_count FROM raw.ittf_player_info WHERE Birth_year IS NOT NULL GROUP BY Birth_year ORDER BY Birth_year LIMIT 50", "purpose": "Check birth year distribution for outliers and impossible values at the low end", "source": "raw"}}