Workflow to Build a Semantic Model

Here are the common tasks for creating and building a semantic model.

Task	Description	More Information
Understand Semantic Modeler	Use Semantic Modeler to create a semantic model and build its physical, logical, and presentation layers.	Introduction to Semantic Models Plan a Semantic Model
Request Permissions to Use Semantic Modeler	Ask your administrator to give you the BI Data Model Author application role. To check you if have permission to use Semantic Modeler, navigate to the Home page, click Create, and look for the Semantic Model option. If you don't see the Semantic Model option, then you don't have the BI Data Model Author application role. If you plan to set up one or more data source connections for your semantic model, ask your administrator to give you the DV Content Author application role.	About Application Roles
Confirm that your data source is supported	Understand which data sources Semantic Modeler supports. Semantic Modeler only supports relational data sources. Before you import a semantic model from Model Administration Tool or Data Modeler, confirm that Semantic Modeler supports the model's data source. Be sure to remove or replace any unsupported data sources in the semantic model before migration. The import fails if a semantic model contains an unsupported data source.	Data Sources Available for Data Modeling
Create the Semantic Model	Create the semantic model in one of the following ways: Create an empty semantic model. Import an exported semantic model (.rpd file), an archived semantic model (.zip file), or an .rpd file from Model Administration Tool. Load the semantic model deployed to Oracle Analytics. Clone a Git repository to your development environment.	Create a Semantic Model Develop Semantic Models in a Collaborative Environment
Build the Physical Layer	Define the semantic model's data sources and the relationships between physical databases and other data sources that the Oracle Analytics query engine uses to process multiple data source queries. Define other attributes of the physical data sources, such as join relationships, that might not exist in the data source metadata. Tasks include: Importing metadata Creating physical tables and columns Creating alias tables Creating joins	Build a Semantic Model's Physical Layer
Build the Logical Layer	Define one or more business model objects that contain the business model definitions and the mappings from logical to physical tables. Create logical tables (fact and dimension) containing logical columns. Tasks include: Examine logical joins Examine logical table sources Rename logical objects Delete unnecessary logical objects Create simple measures	Build a Semantic Model's Logical Layer Work with Logical Hierarchies
Build the Presentation Layer	Structure the logical layer's objects to be presented to users as subject areas that they'll use to build visualizations and analyses. Tasks include: Create presentation tables Create presentation columns Rename and reorder presentation columns	Build a Semantic Model's Presentation Layer
Test and Validate the semantic model	Check the semantic model for errors. Deploy the semantic model. Test the semantic model by creating visualizations and analyses and verifying the results. Tasks include: Check consistency Deploy Create and run visualizations and analyses	Check Consistency and Deploy a Semantic Model