Let me clarify my approach to optimizing complex queries and stored procedures in SQL Server, especially when working with large datasets. First, I always start by reviewing the execution plan to identify bottlenecks, such as missing indexes, expensive joins, or table scans. If I notice that certain queries are running slowly, I check if the right indexes are in place and whether the queries are making use of them. If there are multiple joins, I try to ensure that only the necessary columns are being selected and that filters are applied as early as possible to reduce the data being processed. Sometimes, I break down a large query into smaller, more manageable parts or use Common Table Expressions to simplify logic and improve readability. When dealing with temporary data, I prefer using temporary tables over table variables for larger datasets, since temp tables generally perform better and allow indexing. I also look for opportunities to refactor stored procedures by splitting them into smaller, modular procedures if they become too complex, which helps with both performance and maintainability.Throughout the process, I keep checking the execution plan after each change to see the impact. Additionally, I monitor query statistics and use tools like SQL Profiler or Extended Events to identify slow-running queries in production. By combining these techniques, I’ve been able to significantly reduce query execution times and improve overall system performance.