About this task

Consider the following:

• Unhandled NULL values in key columns will result in incomplete aggregate tables and unexpected query results. See the Custom Empty Member feature for more details.
• Once you have modeled a dimension in any cube in your project, that dimension is saved in the project library and can be reused in other cubes in the project, or in other contexts in the same cube. For example, you may model a common Date dimension that is reused in many different contexts.
• A dimension is not included in a cube until it has a relationship to the fact dataset of the cube (either directly or indirectly). For details, see Modeling Relationships.

More information

• Add a Normal Dimension How to model a logical dimension from a normalized dimension dataset.
• Many-to-Many Relationships: Add a Multi-Valued Dimension How to model a logical dimension from a multi-valued or bridge dimension dataset.
• Add a Degenerate Dimension or a Common Degenerate Dimension How to model a logical dimension off of one or more columns that are in a single fact dataset or in multiple fact datasets.
• Add a Snowflake Dimension In AtScale, a snowflake dimension refers to a logical dimension comprised of columns coming from more than one physical dataset.
• Create a Security Dimension Restrict users to accessing only a subset of data in a cube by creating one or more security dimensions. When users run queries against the cube, AtScale uses the security dimension as a runtime constraint. However, the constraint does not appear as part of the query on the AtScale Queries Search page.