Description: A window function performs a calculation across a set of table rows that are somehow related to the current row. This type of function allows for operations such as sums, averages, or counts, but unlike traditional aggregate functions, it does not collapse rows into a single result. Instead, window functions maintain the granularity of the data, providing results that can be used in more complex analyses. Window functions are defined using the OVER clause, which specifies how rows are grouped for the calculation. This allows data analysts and data scientists to perform more sophisticated calculations and gain deeper insights from the data. Window functions are particularly useful in time series analysis, where moving averages or trends can be calculated over time, as well as in various types of data analysis, where rankings or percentiles can be calculated within a dataset without losing the information of each individual row. In summary, window functions are a powerful tool in the SQL arsenal, enabling efficient and effective complex analysis.
