A Resolve Common Errors in Semantic Model Extensions

You must resolve the detected semantic model errors in time to avoid patch upgrade failures.

If you don't resolve the errors, your pipeline may be disabled, release updates halted, and usability and support may be lost as a result. Use this list of solutions to resolve common errors. Should you continue to experience difficulties after following these solutions, create a service request for comprehensive assistance.

Error: Column missing from augmentation or mapped augmentation column not available

Description: One of your data augmentations is no longer synchronized with its corresponding semantic model extension. This mostly likely occurred because the SME Options for Data Augmentation feature (under the Generally Available Features tab on the Enable Features page) was enabled. For optimal performance and stability, Oracle recommends that you manually configure your semantic model with User Extensions, rather than having the data augmentation automatically generate the system semantic model extensions. The reason for this recommendation is any changes to the underlying data augmentation, that remain referenced in the semantic model, cause your semantic model extensions to become out-of-sync and fail. The recommended practice is to separate the Data Augmentation and Semantic Model Extension process, which provides greater flexibly for complex modelling and prevents errors. Going forward, when creating data augmentations, always use the Dataset type and define your own user semantic model extensions. Don't create any new data augmentations (of type Dimension, Fact, or Extend Entity) that create the system semantic model extensions. If feasible, convert all your existing data augmentations to datasets and user semantic model extensions.

Resolution Tip (if seeing this error in a non-production instance):

1. Reset the data augmentation cache. See Reset the Cache.
2. From the Console in Oracle Fusion Data Intelligence, navigate to Data Configuration, then Data Augmentation. Locate and edit the problematic data augmentation. Continue to the subsequent step to review the selected attributes. Uncheck any attributes no longer available in the source. Navigate through the configurations using Next, then click Finish to save and schedule your changes.
3. Following the completion of the data augmentation process, ensure to refresh and update the semantic model extensions that reference the data augmentation target table to remove any deactivated columns.
   To remove all unreferenced objects, conduct a cleanup of the subject area and logical star as follows:

   1. Create a sandbox.
   2. Edit the subject area to remove any elements that references the deleted columns.
   3. Edit the logical star to delete all associated columns, derived fields, and dimensions. If the dimension is missing from the logical star, re-add and then delete it.
   4. Apply the changes on the sandbox to confirm your changes.
   5. Merge the sandbox to Main.
   6. Publish the updated model.
   7. Re-validate the model to confirm it's error free.

Resolution Tip (if seeing this error in a production instance):

When you find that certain augmentation columns are absent in the production instance, the cause is typically one of two scenarios:

1. The augmentation wasn't deployed: In this scenario, you must run the Data Configuration bundle that includes the expected augmentation.
2. The augmentation was deliberately removed: If the Augmentation was deleted, you must first update the semantic model in the lower environment to remove the reference to it. After removing the reference, redeploy the semantic model bundle to the production instance.

Error: Custom columns have leading or trailing whitespace character

Description: The display name of an attribute, derived column, or physical column begins or ends with a space.

Resolution Tip: This error occurs when the display names of unselected attributes contain leading or trailing spaces. To resolve this:

1. Edit the logical star and select Add attributes for all columns with extra spaces at the beginning or end of their display names.
2. In Display Name, remove any leading or trailing whitespace from the newly selected columns. Click outside the field to save the change.
3. Proceed through the next steps and save your modifications.
4. Apply the changes in your sandbox.
5. Merge the sandbox to the main sandbox.
6. Publish the updated model.
7. Revalidate the model to confirm it's error free.

Note:

The additional selected columns in the logical star won't automatically appear in the user-facing subject area unless you add it explicitly.

Error: Subject area attributes have leading or trailing whitespace character. Please check subject area name/description/folders/columns for possible whitespaces

Description: The display name of a subject area name, description, folder, or column name begins or ends with a space.

Resolution Tip: Edit the subject area, then edit the problematic customization, locate, and remove all leading and trailing spaces on subject area names, descriptions, folders, and column names.

Error: Step is in error state

Description: An error occurred in this step during the semantic model compilation.

Resolution Tip: Edit the failed step, investigate, identify the errors, and resolve them.

Customization steps can be in an error state because the extension's source is no longer accessible. This is indicated by the object drop-down showing "Select" instead of the correct object name when you edit the customization.

Database object not found can happen for the following reasons:

• The instance is missing referenced custom data configurations, including data augmentations, descriptive flexfields (DFFs), and configurable account analysis.
• The database object was never migrated to Autonomous Data Warehouse.
• The necessary permissions, such as GRANT SELECT ON "OAX_USER"."TABLE_VIEW" TO "OAX$OAC", were not applied or have been removed.
• The object name contains unsupported special characters such as parentheses.

Error: Last step in the branch has consistency check errors.

Description: An error occurred during the semantic model compilation.

Resolution Tip: The error indicates a failure in the final step, but the root cause likely lies in an earlier stage. Edit the last failed step, investigate, identify the errors, and resolve them.