OLAP functions, when combined with the GROUPING, CUBE, and ROLLUP extensions, provide two primary benefits. First, they let you perform multidimensional data analysis, data mining, time series analyses, trend analysis, cost allocations, goal seeking, ad hoc multidimensional structural changes, nonprocedural modeling, and exception alerting, often with a single SQL statement. Second, the window and reporting aggregate functions use a relational operator, called a window that can be executed more efficiently than semantically equivalent queries that use self-joins or correlated subqueries. The result sets you obtain using OLAP can have subtotal rows and can be organized into multidimensional cubes. See “Windowing”.
Moving averages and moving sums can be calculated over various intervals; aggregations and ranks can be reset as selected column values change; and complex ratios can be expressed in simple terms. Within the scope of a single query expression, you can define several different OLAP functions, each with its own partitioning rules.
