While querying our databases we might face a typical problema which is getting the next or the previous value of an atribute according to some rule applyed to a certain dataset. This happens more if you deal with datawarehouses and need to retrieve this kind of analytical information. The typical solutions involve several “group by” and sub queries to achieve the same result. This way SQL has a powerful feature which are the Analytical functions.
Analytic functions compute an aggregate value based on a group of rows. They differ from aggregate functions in that they return multiple rows for each group. The group of rows is called a window and is defined by the
analytic_clause. For each row, a sliding window of rows is defined. The window determines the range of rows used to perform the calculations for the current row. Window sizes can be based on either a physical number of rows or a logical interval such as time.