About Working with Logical Hierarchies in a Semantic Model
In the semantic model's logical layer, a dimension object represents a hierarchical organization of logical columns (attributes).
You can associate one or more logical dimension tables with one dimension object.
Common dimensions include time periods, products, markets, customers, suppliers, promotion conditions, raw materials, manufacturing plants, transportation methods, media types, and time of day. Dimensions exist in the logical layer and in the presentation layer.
In each dimension, you organize logical columns into the structure of the hierarchy. The structure represents the organization rules and reporting needs required by your business and provides the metadata the Oracle Analytics query engine uses to drill into and across dimensions to get detailed views of the data.
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Dimensions with level-based hierarchies - These are also called structure hierarchies. In level-based hierarchies, members are of several types, and members of the same type, such as employee or assembly occur only at a single level.
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Dimensions with parent-child hierarchies - These are also called value hierarchies. In parent-child hierarchies, members all have the same type.
Because dimensions for multidimensional data sources are defined in the source, you don't create dimension level keys. A dimension is specific to a particular multidimensional data source. You can't create and manipulate a dimension individually. Each cube in the data source should have at least one dimension and one measure in the logical layer.
You can expose logical hierarchies to workbooks and analyses by creating presentation hierarchy objects that are based on particular logical hierarchies. Creating hierarchies in the presentation layer enables users to create hierarchy-based queries. See Work with Presentation Hierarchies and Levels.
You can also expose hierarchies by adding one or more columns from each hierarchy level to a subject area in the presentation layer.