OLAP Operations

Some typical OLAP operations for multidimensional data are as follows:

•           Roll-up
•          Drill-down
•          Slice and dice
•          Pivot (rotate) 

The roll-up operation (also called the drill-up operation) performs aggregation on a data cube, either by climbing up a concept hierarchy for a dimension or by dimension reduction. In the example given below following points need to be noted.

• ·         Roll-up is performed by climbing up a concept hierarchy for the dimension location.
• ·         Initially the concept hierarchy is "street < city < province < country".
• ·         On rolling up, the data is aggregated by ascending the location hierarchy from the level of city to the level of country.
• ·         The data is grouped into cities rather than countries.
• ·         When roll-up is performed, one or more dimensions from the data cube are reduced. 

Drill-down is the reverse of roll-up. It navigates from less detailed data to more detailed data. Drill-down can be realized by either stepping down a concept hierarchy for a dimension or introducing additional dimensions.

In the above example for Drill Down

•         Drill-down is performed by stepping down a concept hierarchy for the dimension time.
•         Initially the concept hierarchy was "day < month < quarter < year."
•         On drilling down, the time dimension is descended from the level of quarter to the level of month.
•         When drill-down is performed, one or more dimensions from the data cube are expanded.
•         It navigates the data from less detailed data to highly detailed data. 

The slice operation selects one particular dimension from a given cube and provides a new sub-cube. In the following Example

•         Here Slice is performed for the dimension "time" using the criterion time = "Q1".
•         It will form a new sub-cube by selecting one or more dimensions. 

The dice operation defines a sub-cube by performing a selection on two or more dimensions. In the Example below

The dice operation on the cube based on the following selection criteria involves three dimensions.

•          (location = "Toronto" or "Vancouver")
•          (time = "Q1" or "Q2")
•          (item =" Mobile" or "Modem") 

Pivot (also called rotate) is a visualization operation that rotates the data axes in order to provide an alternative presentation of the data. The following example shows this