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Window functions have proven to be a game-changer in SQL as they replace the need for self-joins or subqueries in many scenarios. They allow for more concise and efficient code, reducing the complexity of queries and improving performance.

Window functions are incredibly useful for solving complex analytical problems. They allow you to perform calculations on a specified window, or subset, of rows without altering the result set. For example, you can use window functions to calculate running totals, calculate percentage contribution, or find the top N records within each group.

In addition to the examples mentioned, window functions can also be used for data cleansing and data validation. They can help identify duplicates, detect gaps or overlaps in time series data, and perform various data transformations. Overall, window functions provide a powerful toolset for performing advanced analysis and gaining deeper insights from your data.

While window functions excel at solving analytical problems, they also have a practical use in managing rankings and pagination. By combining window functions with ORDER BY and ROW_NUMBER(), you can easily rank records based on specific criteria. This is particularly helpful when implementing search result pagination or generating leaderboards.