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semantic-model-authoring

Create, edit, deploy, and validate Power BI semantic models.

3|6|Updated Jun 21, 2024
Search Tags:#best practices#fabric#dax#power bi#semantic model#direct lake#tmdl
One-click install
npx skills add https://github.com/rritec/Microsoft-Fabric --skill semantic-model-authoring-rritec
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: semantic-model-authoring
Source: https://github.com/rritec/Microsoft-Fabric/tree/main/skills/plugins/powerbi-authoring/skills/semantic-model-authoring
Command: npx skills add https://github.com/rritec/Microsoft-Fabric --skill semantic-model-authoring-rritec

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you create, edit, deploy, refresh, and validate Power BI semantic models in Fabric and Power BI Desktop without hand-authoring model files.

Core Features & Use Cases

  • Create and structure models: Build new semantic models for Import, DirectQuery, or Direct Lake scenarios with star-schema guidance.
  • Edit and optimize existing models: Add or refine measures, tables, columns, relationships, DAX, permissions, and data-source settings.
  • Deploy and validate: Publish PBIP or TMDL changes to Fabric, refresh datasets, and check best practices, performance, and AI readiness.
  • Use Case: Update a sales model with a new margin measure, deploy it to a workspace, and verify it with a read-only DAX query.

Quick Start

Use the semantic model authoring skill to add a gross margin measure to my Fabric semantic model and validate that it returns the expected result.

Frequently Asked Questions about semantic-model-authoring

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I add a DAX measure to a Power BI semantic model and validate it?▼

You can write and validate DAX measures in a Power BI semantic model by applying TMDL or MCP editing paths, deploying updates to Fabric, and running read-only DAX queries to verify expected results.

What is the best way to build a Power BI Direct Lake semantic model?▼

Building a Direct Lake semantic model requires structuring tables with star-schema guidance and binding data source connections through Fabric REST APIs to optimize performance for Direct Lake scenarios.

Does this Power BI semantic model authoring approach work with PBIP format?▼

Yes, semantic model authoring supports PBIP format, allowing you to publish TMDL changes to Fabric workspaces and refresh datasets directly without hand-authoring model files.

How do I check Power BI semantic models for best practices and AI readiness?▼

You validate Power BI semantic models for best practices and AI readiness by applying guideline-driven validation rules to review modeling, DAX, Direct Lake configurations, and deployment performance.

Can I edit existing Power BI semantic model relationships without manual file authoring?▼

You can edit existing Power BI semantic model relationships, permissions, and data-source settings without manual file authoring by using TMDL or MCP editing paths integrated with Fabric REST APIs.

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