Applies To: SQL Server 2016 Preview
Cubes have a number of properties that you can set to affect cube-wide behavior. These properties are summarized in the following table.
Some properties are set automatically when the cube is created and cannot be changed.
For more information about how to set cube properties, see Cube Designer (Analysis Services - Multidimensional Data).
Specifies the common prefix that is used for aggregation names.
Specifies the locale identifier (LCID) and the comparison flag, separated by an underscore: for example, Latin1_General_C1_AS.
Contains a Multidimensional Expressions (MDX) expression that defines the default measure for the cube.
Provides a description of the cube, which may be exposed in client applications.
Contains configurable error handling settings for handling of duplicate keys, unknown keys, error limits, action upon error detection, error log file, and null key handling.
Specifies the number of estimated rows in the cube.
Contains the unique identifier (ID) of the cube.
Specifies the default language identifier of the cube.
Specifies the user-friendly name of the cube.
Defines proactive cache settings for the cube.
Indicates whether indexing and aggregating should occur during or after processing. Options are regular or lazy.
Determines the processing priority of the cube during background operations, such as lazy aggregations and indexing. The default value is 0.
Indicates whether the script cache should be built during or after processing. Options are regular and lazy.
Determines error handling. Options are IgnoreNone or IgnoreAll
Displays the data source view used for the cube.
Specifies the file system storage location for the cube. If none is specified, the location is inherited from the database that contains the cube object.
Specifies the storage mode for the cube. Values are MOLAP, ROLAP, or HOLAP.
Determines the visibility of the cube.
For more information about setting values for the ErrorConfiguration property when working with null values and other data integrity issues, see Handling Data Integrity Issues in Analysis Services 2005.