powerbi-modeling

by github

Semantic modeling assistant for building optimized Power BI data models with DAX, relationships, and best practices. Connects to active Power BI models (Desktop or Fabric) to analyze current structure before providing guidance on star schemas, relationships, measures, and naming conventions Covers core modeling tasks: creating DAX measures, configuring table relationships and cardinality, implementing row-level security (RLS), and optimizing performance Includes model quality assessment... npx skills add https://github.com/github/awesome-copilot --skill powerbi-modeling Download ZIPGitHub36.2k

Power BI Semantic Modeling

Guide users in building optimized, well-documented Power BI semantic models following Microsoft best practices.

When to Use This Skill

Use this skill when users ask about:

• Creating or optimizing Power BI semantic models

• Designing star schemas (dimension/fact tables)

• Writing DAX measures or calculated columns

• Configuring table relationships (cardinality, cross-filter)

• Implementing row-level security (RLS)

• Naming conventions for tables, columns, measures

• Adding descriptions and documentation to models

• Performance tuning and optimization

• Calculation groups and field parameters

• Model validation and best practice checks

Trigger phrases: "create a measure", "add relationship", "star schema", "optimize model", "DAX formula", "RLS", "naming convention", "model documentation", "cardinality", "cross-filter"

Workflow

1. Connect and Analyze First

Before providing any modeling guidance, always examine the current model state:

1. List connections: connection_operations(operation: "ListConnections")
2. If no connection, check for local instances: connection_operations(operation: "ListLocalInstances")
3. Connect to the model (Desktop or Fabric)
4. Get model overview: model_operations(operation: "Get")
5. List tables: table_operations(operation: "List")
6. List relationships: relationship_operations(operation: "List")
7. List measures: measure_operations(operation: "List")

2. Evaluate Model Health

After connecting, assess the model against best practices:

• Star Schema: Are tables properly classified as dimension or fact?

• Relationships: Correct cardinality? Minimal bidirectional filters?

• Naming: Human-readable, consistent naming conventions?

• Documentation: Do tables, columns, measures have descriptions?

• Measures: Explicit measures for key calculations?

• Hidden Fields: Are technical columns hidden from report view?

3. Provide Targeted Guidance

Based on analysis, guide improvements using references:

• Star schema design: See STAR-SCHEMA.md

• Relationship configuration: See RELATIONSHIPS.md

• DAX measures and naming: See MEASURES-DAX.md

• Performance optimization: See PERFORMANCE.md

• Row-level security: See RLS.md

Quick Reference: Model Quality Checklist

Area Best Practice Tables Clear dimension vs fact classification Naming Human-readable: Customer Name not CUST_NM Descriptions All tables, columns, measures documented Measures Explicit DAX measures for business metrics Relationships One-to-many from dimension to fact Cross-filter Single direction unless specifically needed Hidden fields Hide technical keys, IDs from report view Date table Dedicated marked date table

MCP Tools Reference

Use these Power BI Modeling MCP operations:

Operation Category Key Operations connection_operations Connect, ListConnections, ListLocalInstances, ConnectFabric model_operations Get, GetStats, ExportTMDL table_operations List, Get, Create, Update, GetSchema column_operations List, Get, Create, Update (descriptions, hidden, format) measure_operations List, Get, Create, Update, Move relationship_operations List, Get, Create, Update, Activate, Deactivate dax_query_operations Execute, Validate calculation_group_operations List, Create, Update security_role_operations List, Create, Update, GetEffectivePermissions

Common Tasks

Add Measure with Description

measure_operations(
 operation: "Create",
 definitions: [{
 name: "Total Sales",
 tableName: "Sales",
 expression: "SUM(Sales[Amount])",
 formatString: "$#,##0",
 description: "Sum of all sales amounts"
 }]
)

Update Column Description

column_operations(
 operation: "Update",
 definitions: [{
 tableName: "Customer",
 name: "CustomerKey",
 description: "Unique identifier for customer dimension",
 isHidden: true
 }]
)

Create Relationship

relationship_operations(
 operation: "Create",
 definitions: [{
 fromTable: "Sales",
 fromColumn: "CustomerKey",
 toTable: "Customer",
 toColumn: "CustomerKey",
 crossFilteringBehavior: "OneDirection"
 }]
)

When to Use Microsoft Learn MCP

Research current best practices using microsoft_docs_search for:

• Latest DAX function documentation

• New Power BI features and capabilities

• Complex modeling scenarios (SCD Type 2, many-to-many)

• Performance optimization techniques

• Security implementation patterns