Add a custom department dimension to a prebuilt fact in Oracle Fusion AI Data Platform for accurate slicing and clean aggregation. Explore more Oracle Fusion AI Data Platform resources at the links below.
In this demo, you learn how to use the Semantic Model Extensions framework in Oracle Fusion AI Data Platform to add a custom department dimension to a prebuilt fact in the SCM sales order subject area. The tutorial starts in Autonomous Data Warehouse, where you create the custom dimension table and confirm the join key column is unique so your workbook does not duplicate data.
Next, you grant semantic model access on the department table for the Oracle Analytics Cloud schema so the semantic model can query the new data. From the Oracle Fusion AI Data Platform home page, you open Semantic Model Extensions and work in a sandbox so you can make changes safely before publishing.
You then edit the logical star, add the new department dimension, and define the keys and attributes you want to expose. Even if you do not need drill-down navigation, you still create a required hierarchy with at least one level so the dimension can be added to the subject area. After that, you connect the custom dimension to the prebuilt fact by adding the physical join columns, avoiding naming conflicts, and creating a left outer join with the content level set to detail. You also confirm the custom dimension level is set to detail for correct aggregation behavior.
Finally, you update the subject area to include the new department attributes, apply and publish the changes, and validate the result in a workbook to confirm accurate measures and slicing by department.
Please note: Oracle Fusion Data Intelligence is now called Oracle Fusion AI Data Platform. The product name has changed, and the steps shown in this video remain the same.
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