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Tableau - like Power BI - can be used to make interactive visualizations with different data sources. If you or your organization use both Power BI and Tableau, you might be confronted with scenarios where you want to make a Tableau dashboard from a published Power BI semantic model.

I'm attempting to be objective in my language and information, but my work and articles focus on Power BI. As such, my text might include unintentional biases towards Power BI. Don't consider any opinions or statements below as bona fide facts or promoting one product over another.

You can rename fields: In the Tableau workbook, you can rename fields (dimensions and measures) to other names. This has no effect on the Power BI dataset; Tableau is not doing a write operation.You can create calculated fields: In Tableau, it’s possible to create additional calculations using the dimensions and measures in the Power BI semantic model, already. These are effectively the same as thin-report measures in Power BI. It isn’t possible to create columns.

A Power BI semantic model (formerly a dataset) is often a key, central component in a reporting ecosystem. The semantic model typically contains important business logic in the table structures, relationships and measures. These are used in central reports that deliver insights to data consumers in the business. However, self-service users can also connect to a semantic model to perform their own analyses. This is valuable, as they re-use the logic defined in the semantic model to answer additional questions and address new use-cases. These self-service analyses can be done in a variety of client tools; users aren’t just limited to Power BI Desktop. This flexibility helps users get the most of their Power BI datasets with their skills and tools of choice, and without needing to copy data or rebuild existing logic.