With semantic models, your data becomes unified into a single source of truth, accessible throughout Salesforce. Semantic models provide a way for your data to be interpreted consistently across Salesforce by mapping it to standardized business terms and logic. Semantic models are first-class Salesforce metadata, so they’re available throughout Data 360 to power analytics and data-driven experiences.
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You can create semantic models from scratch, or you can build them off of an existing semantic model. Either way, once you have a semantic model, you can customize it to suit your specific needs. For example, you can rename fields, override relationship definitions, or even create your own metrics.
Semantic models also include a query generator, which allows you to leverage your data to answer key business questions. The query generator sends customizable semantic queries based on your semantic models, so you can get the insights you need quickly and easily.
When you create a semantic model, relationships that were mapped between data model objects (DMOs) in Data 360 are included. This includes relationships that were previously created between objects outside the Semantic Model Builder. Relationships that create circular relationships (relationships that reference the same object multiple times) are removed.
There are two ways to add semantic models in Tableau Next. You can either create a new semantic model, or select a semantic model based on an existing asset.
You can also create semantic models directly in Data 360. For more information, see Create a Semantic Model in Tableau Semantics.
You can also use the Tableau Semantics connector for Tableau Desktop and Cloud to connect and use semantic models in Data 360 just like you can in Tableau Next. For more information, see Salesforce Help: Tableau Semantics Connector.
- Add Semantic Models
Within Tableau Next, create a new semantic model from an existing asset. - Create and Refine Semantic Models with Semantic Modeling (Beta)
Build and fine-tune semantic models faster by describing your analytic goals directly to Semantic Modeling in your workspace. It translates your natural language requirements into fully mapped semantic models and helps refine existing ones. The tool automatically scans your active workspaces to find relevant data objects, create relationships, and generates calculated field formulas. This accelerates your time to insights and removes traditional friction, helping both experienced modelers and less expert users build and refine semantic models without manual configuration. Plus, you can review and adjust all selected data objects and formulas before generating the semantic model. - Accelerate Semantic Model Creation with Marketplace Templates
When developing semantic models to unify and make sense of your enterprise data, you can build a model entirely from scratch or use a pre-configured template. Tableau Next Marketplace semantic model templates are designed to accelerate your development process. - Create a Calculated Field with Einstein
You can use Einstein to easily and effectively create calculated fields within Tableau Next.