After making structural changes to a cube, you must process the cube before attempting to browse its data. Process your cube after completing any of the following:
- Building the cube and designing its storage options and aggregations
- Changing the cube's structure (measures, dimensions, and so on) and saving the changes to the cube
- Changing the structure of a shared dimension used in the cube
Also, if data in the cube's data warehouse has been added or changed, processing is recommended in order to ensure accurate results when browsing the cube.
When you process a cube, the aggregations designed for the cube are calculated and the cube is loaded with the calculated aggregations and data. Processing a cube involves reading the dimension tables to populate the levels with members from the actual data, reading the fact table, calculating specified aggregations, and storing the results in the cube. After a cube is processed, users can query it.
There are three ways to process a cube. If you are modifying the structure of the cube, you may be required to process the cube with the Full Process option. If you are adding new data to the cube, you can process the cube with the Incremental update option. To clear out and replace a cube's source data, you can use the Refresh data processing option.
In addition to these three mutually exclusive options, a fourth option can be selected in conjunction with any of these options. This option allows you to incrementally update the cube's dimensions as part of the cube processing. This option is called incrementally update the dimensions of this cube.
These options are available in the Process a Cube dialog box, which is displayed when you right-click a cube in the Analysis Manager tree pane and then click Process.
Processing a cube can take a great deal of time, especially for complex cubes with dimensions containing millions of members. Frequently processing cubes based on rapidly changing data, such as data found in online transaction processing (OLTP) databases, can be a difficult task. Very often such cubes contain stale data, with aggregations based on a view of the data that is no longer valid.
Real-time OLAP provides a way to automatically process the relational OLAP (ROLAP) dimensions and/or partitions based on Microsoft® SQL Server™ 2000 relational tables when changes to the underlying dimension or fact tables occur. This allows real-time cubes based on rapidly changing data to be automatically updated and always available to end users. For more information about real-time cubes, see Real-Time Cubes.