Top FAQs for Customization and Data Augmentation

Can I customize the prebuilt Oracle content?

Yes, you can customize the prebuilt Oracle content through semantic model customization.

Does Oracle Fusion Data Intelligence extract all data from Oracle Fusion Cloud Applications?

Oracle Fusion Data Intelligence comes with a base semantic model with prebuilt metadata. Data pipelines extract data and load the prebuilt tables for all the activated functional areas. Data augmentation enables you to bring any custom data into Oracle Fusion Data Intelligence.

Why are some of my data augmentations, custom data configurations, and functional areas rejected?

When incremental job runs, the system extracts data for all the modules (data augmentations, custom data configurations, and functional areas) that are activated. If you've activated any data augmentation before the next incremental run or marked with Reset Data, then the system fetches the data for these modules in full. It's possible to not get data for some of the data augmentations either because of new columns added or some issue with extraction. In that case, the system rejects those data augmentations, custom data configurations, and functional areas.

Where can I find the semantic model customization best practices?

See About Recommendations and Tips to Extend the Semantic Model.

Can I extend Oracle Fusion Data Intelligence with custom public view objects (PVOs)?

Yes, you can extend Oracle Fusion Data Intelligence with custom PVOs. Refer to Fusion Data Intelligence Extension with Custom PVOs for additional details.

Can I create custom data models with the semantic model framework?

Yes, you can create custom data models using the semantic model framework. Refer to Custom Data Model Use Case for additional details.

Does Oracle Fusion Data Intelligence provide all descriptive flex fields (DFFs)?

Oracle Fusion Data Intelligence data pipelines don't bring in all DFFs for performance reasons. Ensure that you configure the DFF mapper that provides the ability to select only the DFFs and attributes that are required for reporting purposes. See Enabling Descriptive Flexfields in Oracle Fusion Data Intelligence for more information on configuring the DFF mapper.

When I use the DFF mapper, do I get custom DFFs too?

Yes, you get custom DFFs as long as they are BI Enabled as outlined in Enabling Descriptive Flexfields in Oracle Fusion Data Intelligence.

Do I get access to the repository file?

The semantic model in Oracle Fusion Data Intelligence doesn’t expose the repository file. However, you can use the Oracle Fusion Data Intelligence Console to define the external connections to the repository file.

Why are the column changes not reflected immediately after updating an existing augmentation?

Changes are visible after the next incremental run.

Why am I seeing the message “There Are Pending System Requests"" while publishing a model after activating all the modules successfully?

You're seeing this message because after every module activation, the customization steps are reapplied. Because the last module activation completed recently, the publishing request is in queue. Oracle Fusion Data Intelligence processes the pending requests shortly.

Why does it take a long time sometime to modify the subject area step while extending the semantic model?

The replicated subject area normally inherits everything from the parent subject area such as permissions and roles. Hence, depending on the size of the subject area, it takes a while to complete.

Can external application and augmentation co-exist if you've augmentation on the same object that is part of the skeleton semantic model used for external application?

External application and augmentation can't co exist. If you've augmentation on the same object that is part of the skeleton semantic model used for external application, then you must move those augmentations to the external semantic model.

Why do I see my data augmentations with no data in the public view object (PVO) in “Rejected” status?

The system automatically rejects data augmentations with zero records. You must ensure that the underlying PVO contains data before creating data augmentation and semantic model extensions on top of it.