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In the world of Database Management Systems (DBMS), MySQL 8.0 has made a significant impact by introducing a myriad of new features. One such feature, which we will discuss today, is the Window Functions. They perform a calculation across a set of table rows that are somehow related to the current row, offering greater flexibility and ease in data analysis. Window Functions are now supported by many DBMS, including SQL Server 2019, MySQL 8.0, DB2 11.5, Azure SQL, and Azure Synapse.

To give an overview, Window Functions are SQL functions that perform operations on a set of rows and return a single value for each row from the underlying query. The term 'window' describes the set of rows on which the function operates. A window function uses values from the rows in a window to calculate the returned values. They can perform operations such as calculations for moving averages, running totals, or cumulative sums.

Let’s take a look at a simple example using MySQL 8.0. Suppose we have a table "sales" with columns "year", "month", and "revenue". If we want to calculate the cumulative revenue for each month, we can use the SUM window function as follows:

SELECT year, month, revenue,
SUM(revenue) OVER (PARTITION BY year ORDER BY month) as cumulative_revenue
FROM sales;

In the above example, the PARTITION BY clause divides the result set into partitions (in this case year). The window function is applied to each partition separately and computation restarts for each partition. The ORDER BY clause orders the rows in each partition.

Window Functions are not only limited to MySQL. In SQL Server 2019, for example, you can use the LAG window function to access data from a previous row without using a self-join. Here's how you can use it to compare the sales of the current month with the previous month:

SELECT year, month, revenue,
LAG(revenue, 1, 0) OVER (ORDER BY year, month) as prev_month_revenue
FROM sales;

The LAG function fetches the value of the previous row in the window frame. If there is no previous row, it returns the default value specified (in this case 0).

Window Functions are a powerful tool in SQL, providing advanced capabilities for complex computations and data analysis. They are particularly helpful when dealing with time series data, top-N-queries, and cumulative sums. With support from platforms such as MySQL 8.0, SQL Server 2019, DB2 11.5, Azure SQL, and Azure Synapse, SQL professionals can leverage Window Functions for a variety of tasks, improving efficiency and productivity.

In conclusion, the introduction of Window Functions in MySQL 8.0 and their support in other DBMS have brought significant improvements in the way we perform calculations and analyze data. They provide a more efficient, flexible, and powerful way to perform operations that would otherwise require complex subqueries and self-joins. Therefore, mastering Window Functions is a must for any SQL professional wanting to leverage the full potential of these modern DBMS.