Advantages of a Time-based Partitioned Cube

Time-based partitioned cubes are similar, but superior, to standard cube groups, in that they

• offer a faster, more efficient way of building and updating time-segmented data than incrementally updated cubes

  New data is typically added to a single partitioned cube, rather than to a large existing cube.

• eliminate the periodic need to do a full build, resulting in shorter down-times for the production system, and a more easily managed maintenance schedule
• support rolling time periods

  You can manually edit the .vcd file to remove references to cubes that are no longer required, and drop invalid or out-of-date categories. The control cube and definition file are automatically updated with the newest categories and cube references. For more information, see Customizing a Time-based Partitioned Cube.

• support slowly changing dimensions

  Existing child cubes retain the history, and new cubes are easily created using the Move capability for categories.

• offer better query performance, because users drilling down into the time dimension encounter fewer cubes

  When report users reach the level of granularity that the cubes are based on, such as January or Q1, they only need to access a single cube.

• offer more flexibility

  Although time-based partitioned cubes relate to only one level of granularity, such as Month, you can still reference other time levels in the same model or cube if this improves run-time performance.