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edwardpcharles
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dax-optimize

Analyzes VertiPaq timing of Power BI DAX expressions and provides rewrite suggestions with Microsoft Learn documentation.

3|Updated Mar 28, 2026
Search Tags:#optimization#performance analysis#Microsoft Learn#DAX#Power BI
One-click install
npx skills add https://github.com/edwardpcharles/Agents-Skills --skill dax-optimize
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: dax-optimize
Source: https://github.com/edwardpcharles/Agents-Skills/tree/main/dax-optimize
Command: npx skills add https://github.com/edwardpcharles/Agents-Skills --skill dax-optimize

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python, powershell, .net, adomd.net, amo, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill automates Power BI DAX optimization by leveraging VertiPaq timing analysis and Microsoft Learn documentation for guidance.

Core Features & Use Cases

  • DAX Timing Analysis: Perform detailed timing analysis of DAX queries to identify bottlenecks.
  • Microsoft Learn Integration: Access relevant DAX documentation from Microsoft Learn for deeper insights.
  • DAX Rewrite Suggestions: Offer optimized DAX expressions based on analysis results.
  • Use Case: When you have a complex DAX measure that runs slowly, use this Skill to analyze the measure's performance, identify potential issues, and receive recommendations for optimization.

Quick Start

To optimize a DAX measure, use the dax-optimize skill with the command: /dax-optimize optimize measure my_measure_name

Frequently Asked Questions about dax-optimize

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

FAQPage Schema
How do I analyze VertiPaq timing to optimize slow DAX measures in Power BI?▼

To optimize DAX measures, you analyze VertiPaq timing to identify query bottlenecks and receive rewrite suggestions. This process leverages Microsoft Learn documentation to provide performance and readability enhancements for complex expressions.

What is the best way to rewrite DAX expressions for better Power BI performance?▼

The best way to rewrite DAX expressions is by automating VertiPaq timing analysis to pinpoint inefficiencies. This approach provides targeted DAX rewrite suggestions based on detailed performance metrics and Microsoft Learn guidance.

Do I need Python and PowerShell to run automated DAX performance analysis?▼

Yes, you need Python and PowerShell to run automated DAX performance analysis. Execution also requires .NET Analysis Services assemblies, including ADOMD.NET and AMO, to interact with the VertiPaq engine and process timing data.

How does Microsoft Learn integration help with Power BI DAX optimization?▼

Microsoft Learn integration helps with DAX optimization by providing relevant documentation directly alongside timing analysis results. It offers deeper insights into query behavior and supports recommendations for improving model performance and readability.

Can I use this approach to identify bottlenecks in complex DAX queries?▼

Yes, you can use this approach to identify bottlenecks in complex DAX queries. The automated timing analysis evaluates VertiPaq engine performance metrics to expose slow-running measures and suggest optimized DAX rewrites.

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