Add Dimensions to Models
This section explains how to add the different kinds of dimensions in AtScale, and create the relationships needed to include them in a model. The process is slightly different depending on the type of dimension you are modeling.
When modeling dimensions, consider the following:
- Unhandled
NULLvalues 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 model, that dimension is saved in the repository and can be reused in other models, or in other contexts in the same model. For example, you may model a common Date dimension that is reused in many different contexts.
- A dimension is not included in a model until it has a relationship to the fact dataset of the model (either directly or indirectly). For details, see Modeling Relationships.
📄️ Add a Normal Dimension
This section explains how to model a logical dimension from a normalized dimension dataset.
📄️ Many-to-Many Relationships: Add a Multi-Valued Dimension
This section explains how to model a logical dimension from a multi-valued or bridge dimension dataset.
📄️ Add a Degenerate Dimension
This section describes how to model degenerate dimensions, which are logical dimensions based on one or more columns in one or more fact datasets.
📄️ Add a Snowflake Dimension
In AtScale, a snowflake dimension refers to a logical dimension made up of columns coming from more than one physical dataset.
📄️ Using Constraint Translation for Fact Table Query Acceleration
Constraint translation is a Public Preview feature.