Most data sets of multidimensional databases have two characteristics:
- Data is not smoothly and uniformly distributed.
- Data does not exist for the majority of member combinations. For example, all products may not be sold in all areas of the country.
Essbase maximizes performance by dividing the Essbase - Standard dimensions of an application into two types: :
- dense dimensions
- and sparse dimensions.
To know more about this two terms : Dimensional Data Modeling - What means Data is dense/sparse ?
This division allows Essbase to cope with data that is not smoothly distributed, without losing the advantages of matrix-style access to the data. Essbase speeds data retrieval while minimizing memory and disk requirements.
Essbase - Attribute dimensions dimensions are always sparse dimensions.
By default, a new dimension is set sparse.