Set an Aggregation Level Based on a Dimension for a Measure Column

The majority of measures have the same aggregation rule for each dimension. Some measures can have different aggregation rules for different dimensions.

For information about setting up dimension hierarchies, see About Level-Based Hierarchies and About Parent-Child Hierarchies.

For example, a bank could calculate account balances averages over a specific time, but calculated averages on individual accounts with a simple summation for a period. You can configure dimension‐specific aggregation rules. You can specify one aggregation rule for a given dimension and specify other rules to apply to other dimensions.

Choose Based on dimensions as the measure column's aggregation rule if your measure has different aggregation rules for different dimensions, for semi-additive measures.
When setting up the aggregation, selecting the Data is dense option indicates that all sources that the column is mapped to have a row for every combination of dimension levels that they represent. Incorrect results are returned if you select this option and the measure column's table source doesn't contain dense data.
  1. On your home page, click Navigator Navigator icon and then click Semantic Models.
  2. In the Semantic Models page, click a semantic model to open it.
  3. Click Logical Layer Logical layer icon.
  4. In the Logical Layer pane, browse for the table with the logical column that you want to add an aggregation rule to.
  5. In the logical table, click the Columns tab.
  6. In the column table, click the column to highlight it, and then click Detail view to view its properties.
  7. In the logical column's Aggregation properties, click the Aggregation Rule field and select Based on dimensions.
  8. Click Add Aggregate by Dimension and in the dimension field select a dimension.
  9. Click the Formula list and select an aggregation rule, or click the Expression Builder icon to use the Expression Editor to create the aggregation rule.
  10. If all the logical table sources that the column is mapped to are dense, then select the Data is dense field.
  11. Click Save.