With inputs from
- Manjunath Subramanian ,Senior Principal Product Manager
- Navnit Mishra , Consulting Member Of Technical Staff, Customer Excellence, Analytics
- Hiteshkumar Patel ,Senior Principal Product Manager
Related blog : Creating a custom subject area on external data (non-fusion data)
What you’ll learn
The document describes how to extract data from Fusion through data augmentation in FAW and then use it to build new subject areas .
If your use case is
The basic procedure
The steps you’ll need to take include:
- Prerequisite for custom public view objects
- Understanding the source data
- Data Augmentation process
- Data modeling tweaks for a star schema
- Model using Semantic Model Extension
- Create branch
- Create subject area for Quotes
- Create dimensions
- Extend dimension
- Create fact
- Modify subject area
- Re-use the Quotes subject area to create Consumption subject area
- Add dimensions in the Consumption subject area
- Add facts in the Consumption subject area
- Create custom subject area referencing the prebuilt custom Quotes subject area
- Create missing dimensions in the Consumer subject area
- Publish the model
- Validate the model
- Deploy the model
Each of these steps are explained and illustrated in the case study, and we hope you find the information beneficial.
If you have any questions about this procedure or your configuration, please feel free to contact us. The Oracle Analytics team is always happy to lend a hand.
Schedule a meeting today to talk to the Oracle Analytics product team and learn more about how you can extend Oracle Fusion Analytics Warehouse to include data from external sources.

