Have you worked on any other window functions?

Window functions allow you to perform calculations across a set of table rows that are related to the current row, without collapsing the result set into a single row like a traditional aggregate. They are defined using the OVER clause and can be used for ranking, cumulative sums, moving averages, percentiles, and more. For example, ROW_NUMBER() OVER (PARTITION BY dept ORDER BY salary DESC) assigns a unique rank within each department based on salary, while RANK() and DENSE_RANK() handle ties differently. LAG() and LEAD() let you access preceding or following rows, and FIRST_VALUE() / LAST_VALUE() retrieve boundary values. These functions are powerful for analytical queries because they preserve row-level detail while providing context. They are often used in reporting, trend analysis, and data quality checks. Unlike aggregates, window functions do not collapse rows, so you can combine them with regular columns in the SELECT list. Performance can be improved by ensuring appropriate indexes on the partition and order columns, and by using the right function for the job.