Identify the two true statements about a sparse Entity dimension In Hyperion Planning.
A.
You cannot build alternate rollups or assign custom attributes.
B.
Base currencies are assigned to entity members.
C.
Exchange rates are assigned to entity members.
D.
Entity along with Scenario and Period make up a planning unit.
E.
Entity along with Scenario and Version make up a planning unit.
Explanation:
E: The Scenario and Version dimensions represent the broadest categories of data in your application.
Scenario describes the type of data that a plan includes, such as budget, actual, or forecast, as well as the time
span that the plan covers.
Version allows for flexibility and iterative planning cycles. For example, your application could have twoversions, Working and Final, for each scenario. You can also use versions to model possible outcomes based
on different assumptions about interest rates, growth rates, and so on. For example, your application an have a
Best Case and Worst Case version for each scenario.
Note:
Essbase maximizes performance by dividing the Essbase – Standard dimensions of an application into two
types:
dense dimensions
sparse dimensions.
Sparse and dense are a property of the values of an attribute.
Sparse
Data is normally stored in sparse form. If no value exists for a given combination of dimension values, no row
exists in the fact table. For example, if not every product is sold in every market. In this case, Market and
Product are sparse dimensions.
It’s why in the reporting tool Obiee for instance, by default, data are considered sparse.
Dense
Most multidimensional databases may also contain dense dimensions. A fact table is considered to have dense
data if it has (of a high probability to have) one row for every combination of its associated dimension levels.