Semantic Models in Tableau Semantics

Semantic Models are first—class Salesforce metadata, integrated throughout Data 360 to power analytical and data-driven experiences. The semantic model includes definitions tailored for a specific analytical use case. The model can have one or more data objects. You can create flexible joins and unions across objects and enrich your analysis with calculated dimensions and measures.

• Create a Semantic Model in Tableau Semantics
  Create a semantic model to serve specific business needs directly from Data 360. There are three ways to create a semantic model: start from scratch, extend an existing semantic model, or build it using a Data 360 data kit.
• Create a Semantic Model Based on an Existing Model
  Use an existing model and extend it, otherwise known as composability or extensibility, by adding data objects and semantic definitions. When you base a model on an existing model, the new model stays connected to the original model, and the original model remains the single source of truth. Changes made to the original model are automatically added to the extended model, but changes made to the extended model aren’t pushed to the original model.
• Create a Semantic Model from a Data Kit
  To create consistent semantic models, use a data kit. A data kit includes all the semantic definitions, such as the data objects, their relationships, parameters, calculated fields, and metrics. However, a data kit doesn’t include dependencies like data streams and calculated insights.
• Create a Semantic Model from a Tableau Published Data Source (PDS)
  Connect Tableau Published Data Sources (PDS) directly to the Semantic Layer to explore Tableau Next using your existing Tableau content, without any data or metadata migration.