Data Load Differences for ASO

Loading data to Essbase aggregate storage cubes differs from block storage. Data loads only to stored, level-0 members. Temporary buffers help streamline flows from multiple sources, and slices can be merged and replaced. Date format strings help load to date-time dimensions. Aggregations cause recalculation post data load.

Table 35-4 Data Load Differences Between Aggregate Storage and Block Storage

Data Load Functionality	Aggregate Storage	Block Storage
Cells loaded through data loads	Only level 0 cells whose values do not depend on formulas in the outline are loaded	Cells at all levels can be loaded (except Dynamic Calc members)
Update of database values	At the end of a data load, if an aggregation exists, the values in the aggregation are recalculated	No automatic update of values. To update data values, you must execute all necessary calculation scripts.
Data load buffers	The loading of multiple data sources into aggregate storage databases is managed through temporary data load buffers	Not supported
Atomic replacement of the contents of a database	When loading data into an aggregate storage database, you can replace the contents of the database or the contents of all incremental data slices in the database	Not supported
Data slices	Aggregate storage databases can contain multiple slices of data. Data slices can be merged	Not supported
Dimension build for shared members	Full support for parent-child build method. Duplicate generation (DUPGEN) build method limited to building alternate hierarchies up to generation 2 (DUPGEN2).	Support for all build methods
Loading data mapped to dates	In a date-time dimension, you can load data into level 0 members using supported date-format strings instead of member names	Date-time dimension type is not supported
Renegade members	Supported	Not supported
Load rules and impact on existing values	Using load rules with the aggregate storage data load buffer, you can choose to overwrite all the cube data, or replace one slice at a time. Slices can be incrementally gathered into the data load buffer before they are loaded to the database.	Using load rules for block storage, you choose for each source of data whether to overwrite existing values, add values to existing values, or subtract values from existing values.