Power BI

분석

Neotask이 OpenClaw를 통해 Power BI 데이터를 활용합니다 — 의미론적 모델을 자연어로 쿼리하고, 데이터 모델을 구축하며, 자동화된 비즈니스 보고서를 실행합니다.

할 수 있는 것

With 24 actions across two Power BI MCP servers, Neotask through OpenClaw covers both semantic model querying and data model building.

Remote MCP — Query & Analysis (3 actions)

  • `Get Semantic Model Schema` — Understand the structure of any Power BI semantic model
  • `Generate Query` — Create DAX or MDX queries from natural language descriptions
  • `Execute Query` — Run queries directly against your semantic model

    • Modeling MCP — Data Model Management (21 actions)

    Full control over Power BI semantic model structure through conversation:

  • Connection and database operations
  • Table, column, and measure management
  • Relationship creation and management
  • DAX query execution and tracing
  • Calculation groups, hierarchies, security roles
  • Perspectives, named expressions, and cultures
  • Object translations and calendar operations

    • 모든 액션은 자율적으로 실행되거나 승인을 요청합니다 — 여러분이 결정합니다.

    이렇게 물어보세요

  • "Query the Sales semantic model: total revenue by product category for Q1 2026 versus Q1 2025"
  • "Generate a DAX measure that calculates 30-day rolling average sales and add it to our Revenue table"
  • "What tables and measures are available in our Financial Reporting semantic model?"
  • "Create a relationship between the Orders table and the Customers dimension on CustomerID"
  • "Add a security role to our Finance model that restricts the European team to only seeing EU data"
  • "Run this DAX query against our HR model: average headcount by department for each month this year"
  • "Build a calculation group for our time intelligence measures: MTD, QTD, and YTD variants"
  • "What's the query performance like for our largest semantic model? Show me trace data."

    • 프로 팁

  • Schedule automated morning reports that query Power BI semantic models and post key metrics to leadership Slack channels — your data reaches decision-makers without anyone opening Power BI.
  • Enable approval gates on measure and relationship creation — changes to your semantic model affect all downstream reports and deserve review.
  • Connect Power BI with Snowflake in an app group: when new data lands in the warehouse, agents refresh the relevant Power BI datasets and post confirmation to the ops channel.
  • Multi-agent teams can run complete BI development cycles: one agent builds the data model, another creates measures, and a third validates the calculations before publishing.
  • The Generate Query action is powerful for ad-hoc analysis — describe what you need in plain English and agents generate the correct DAX without you writing it.

    • Works Well With