Neotask이 Neotask를 통해 Power BI 데이터를 활용합니다 - 의미론적 모델을 자연어로 쿼리하고, 데이터 모델을 구축하며, 자동화된 비즈니스 보고서를 실행합니다.
Power BI 의미론적 모델을 일반 언어로 쿼리하고 즉시 결과를 얻습니다
대화로 Power BI 데이터 모델을 구축하고 수정합니다 - 측정값, 관계, 계산된 컬럼을 추가합니다
Power BI 데이터를 일정에 맞게 쿼리하고 결과를 슬랙이나 이메일로 게시하는 자동화된 비즈니스 보고서를 실행합니다
할 수 있는 것
With 24 actions across two Power BI MCP servers, Neotask 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.