About Fact Tables


Fact tables are combined with dimension tables to make up star schemas. Fact tables describe events using numeric data. Dimension tables provide detail data that describe the events. Examples of factual events include the sale of an item or a transaction in a bank account. Each such event is represented by a single row in a fact table.
The columns in a fact table consist of one or more numeric columns that relate to an event and a series of foreign key columns that connect the event to the detail data in the dimension tables.

About the Loading of Fact Tables with the Lookup Transformation

To load data into a fact table, use the Lookup transformation in a SAS Data Integration Studio job. The Lookup transformation generates primary key values, loads numeric fact data from a source table, and loads foreign keys from dimension tables using a lookup process.
The lookup process runs separately for each dimension table that contributes foreign keys. The process compares business key values between the source table and a dimension table. If a match is found, an expression (a WHERE clause) is evaluated to identify the specific dimension table row in that business key. In general, the values that are loaded from the dimension table are the primary key columns. Loading these foreign keys into the fact table allows each event to contain references to all of the detail data that describes that event.
If no match is found in a dimension table, or if a value is missing, then the numeric data in the source row is not loaded into the fact table and the exception condition is processed by the Lookup transformation. Each exception condition triggers one or more available actions, including the termination of the job, the loading of source data into an error table, and the loading of information into an exception table.