Build a Power BI Dashboard from a Prompt using AI Agents? (You’re Using MCP Wrong) скачать в хорошем качестве

Build a Power BI Dashboard from a Prompt using AI Agents? (You’re Using MCP Wrong)

Stop copy-pasting DAX from ChatGPT. In 2026, AI Agents can build your Power BI semantic model using MCP. This isn't just a "chat" video. This is a deep dive into Agentic Modeling: the professional workflow for using AI Agents inside Power BI to build, edit, and validate complex models via the new Model Context Protocol (MCP). Most developers are getting the "Power BI AI" story wrong because they don't realize there are TWO separate MCP servers. If you're trying to build a model using the Remote server, or trying to query using the Modeling server... you're having a bad time. In this walkthrough, we go beyond basic DAX generation. We use AI Agents and MCP to structure a production-ready semantic model including a dedicated Measures table, a clean “Measures” display folder, and a full suite of Time Intelligence calculations all applied safely through a PBIP + TMDL workflow. 🕒 TIMESTAMPS 0:00 The "One Prompt" Dashboard Demo 2:15 Modeling vs. Remote MCP (The Biggest Confusion) 4:45 Why PBIP and TMDL are the secret to AI Modeling 7:30 Setting up VS Code, Agent Mode, and the MCP Extension 10:15 Demo 1: Bulk Metadata and Documentation (The Safe Win) 13:00 Demo 2: Building a Proper Date Table & Time Intelligence Measures 16:30 Demo 3: Cleaning Technical Debt and Refactoring DAX 18:45 Safety, Privacy, and The "CFO Guardrail" 20:15 The 2026 Professional AI Workflow 🧠 WHAT WE’RE COVERING ✅ The “Magic” Prompt : Triggering an AI Agent to build your semantic model backbone ✅ Modeling vs Remote MCP : Why one edits your file and the other just “talks” to it ✅ A Dedicated Measures Table : Creating a clean CALCULATE-based measures table ✅ Display Folders : Organizing all measures inside a proper “Measures” folder ✅ Full Time Intelligence Suite : YTD, MTD, QTD, YoY, YoY%, PY, and rolling calculations ✅ Date Table Enhancement : Expanding a Python-generated date table with all calendar attributes ✅ PBIP & TMDL : How AI reads and modifies Power BI project files safely ✅ The Safety First Workflow : Using Git diffs to ensure the AI didn’t break your logic ✅ Secure Usage : Why MCP does NOT send your dataset rows to the open internet 🛠️ THE SETUP VS Code GitHub Copilot (Agent Mode enabled) Power BI Desktop (Must be running) Power BI Modeling MCP Extension Project Format: Save your file as .pbip (Power BI Project) 💡 THE PROMPT FORMULA (Copy and Use) Discover: "List all tables and existing measures." Plan: "Propose a plan to add time intelligence measures, organize them into a dedicated measures table, and enhance the Date table. Do not apply yet." Execute: "Apply the changes using the Modeling MCP tool." Validate: "Check the model for DAX errors, circular dependencies, and folder organization." Plan → Confirm → Apply → Validate. AI moves the gears. You hold the blueprint. 🔗 RESOURCES Power BI Overview : https://learn.microsoft.com/power-bi/ Power BI Projects (.pbip format) : https://learn.microsoft.com/power-bi/... Tabular Model Definition Language (TMDL) : https://learn.microsoft.com/analysis-... GitHub Copilot : https://github.com/features/copilot Power BI Desktop : https://powerbi.microsoft.com/desktop/ 📩 WANT THE DATASET AND PYTHON SCRIPT? If you want the Python data extraction code used to generate and prepare the retail dataset including the initial Date table source reach out directly: 📧 careforce@electrixdata.com Subject Line: “Power BI MCP Python Script” #PowerBI #AI #DAX #MCP #MicrosoftFabric #DataEngineering #GithubCopilot #PowerBIProject #SemanticModel #PBIP #TMDL #TimeIntelligence #BusinessIntelligence