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Defining Dimensions

Objective

After completing this lesson, you will be able to explain the difference between dimensions and measures, and private and public dimensions.

Dimensions and Measures

In SAP Analytics Cloud, dimensions usually represent qualitative master data. Product, cost center, and employee are all examples of dimensions. A model can, and typically does, have several dimensions.

A measure represents transactional or quantitative data; for example, price, revenue, number of customers. Measures are distinct from dimensions, so you can add and configure multiple measures with aggregation and units to fit your data.

In an account-based model, all the numeric values are stored in a single default dimension usually named Account, and you use the financial account structure to determine what each value represents. You can also add calculations, specify units, and set aggregation types for those values. Semantically, an Account dimension type may be referred to as a measure because it fulfills a similar purpose; however, it is really a dimension.

A table of data with columns for dimensions and measures

Note

A measure-based model also supports the account-based single measure dimension, but you can add other measures to the model as well. With the account-based model, you are limited to the single account-type dimension to represent measures.

Private and Public Dimensions

Dimensions can be private or public.

Public dimensions are stand-alone entities that are created independently and can be shared among multiple models. If a model that contains a public dimension is deleted, the public dimension remains intact because it is not dependent on the model. If you copy a model that contains public dimensions, those dimensions are not duplicated, again, because they are not dependent on the model.

Typically, the values for the dimension members are imported into the dimension. Because the data is imported, it is often scheduled to repeat the import process on a regular basis to ensure that the dimension always reflect accurate information.

Private dimensions are created directly in a model, so they are model-specific and cannot be shared among other models. If the model containing the private dimension is deleted, the dimension is also deleted because it is part of the model. The same is true if you copy the model; the private dimension is duplicated in the copy.

Since the dimension is created during the model creation process, the data values for the dimension members are not populated until the data for the entire model structure is imported into it. And while data imports into models can be scheduled, the private dimension cannot be singled out for its own scheduled import.

The dialog when creating a public dimension and the dialog when creating a private dimension

Public dimensions are used much more frequently in SAP Analytics Cloud modeling than private dimensions simply because of their versatility. As independent entities, they can be managed and used much more easily than private dimensions. Private dimensions, however, are excellent choices for single- or infrequent-use situations.

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