Identify the Logical Fact Tables

The semantic model's logical layer contains logical fact tables containing measures with aggregations built into their definitions.

Logical fact tables are different from physical fact tables in relational models. Physical tables in relational models define facts at the lowest possible grain. Logical fact table can contain measures of different grains,

You must define measures aggregated from facts in a logical fact table. Measures are calculated data such as dollar value or quantity sold. You can specify measures in terms of dimensions. For example, you might want to determine the sum of dollars for a given product in a given market over a given time period.

Each measure has its own aggregation rule such as SUM, AVG, MIN, or MAX. A business might want to compare values of a measure and need a calculation to express the comparison. You can specify aggregation rules to specific dimensions. You can define complex, dimension-specific aggregation rules in the semantic model.

You don't explicitly label tables in the logical layer as fact tables or dimension tables. The Oracle Analytics query engine treats tables at the one end of a join as dimension tables, and tables at the many end of a join as fact tables.

The image shows the many-to-one joins to a fact table in a logical diagram. In the logical diagram, all joins have an arrow, indicating the one side, pointing away from the fact table. No joins are pointing to it.

Description of the illustration logical_layer_table_diagram.png