powerbi-modeling
github/awesome-copilot
Power BI semantic modeling assistant for building optimized data models with DAX, relationships, and best practices.
What is powerbi-modeling?
Guides users in designing and optimizing Power BI semantic models following Microsoft best practices. Use when creating measures, designing star schemas, configuring relationships, implementing RLS, or tuning model performance. Connects to active models via MCP tools to analyze structure before providing guidance.
- Analyzes current Power BI model structure and identifies optimization opportunities
- Creates and updates DAX measures with proper naming and documentation
- Designs and validates star schemas with dimension/fact table classification
- Configures table relationships with correct cardinality and cross-filter direction
- Implements row-level security (RLS) roles and permissions
- Provides model quality assessment against best practices checklist
How to install powerbi-modeling
npx skills add https://github.com/github/awesome-copilot --skill powerbi-modeling- Power BI Modeling MCP Server configured and running
- Active Power BI Desktop instance or Fabric workspace connection
- Microsoft Learn MCP Server (optional, for researching latest best practices)
How to use powerbi-modeling
- 1.Connect to your Power BI model using the connection_operations tool
- 2.Run model analysis to list tables, relationships, and measures
- 3.Compare current model against the best practices checklist
- 4.Request specific guidance on areas needing improvement (e.g., star schema design, DAX measures)
- 5.Apply recommended changes using the appropriate MCP operations (measure_operations, relationship_operations, etc.)
- 6.Document tables, columns, and measures with descriptions for clarity
Use cases
- Building a new semantic model from scratch with proper star schema design
- Optimizing an existing model by adding explicit measures and improving relationships
- Implementing row-level security to restrict data access by user role
- Creating calculation groups and field parameters for dynamic calculations
- Documenting tables, columns, and measures with descriptions for report users
- Power BI data modelers
- Business intelligence developers
- Analytics engineers building semantic layers
- Data architects designing Fabric models
- Report developers optimizing model performance
powerbi-modeling FAQ
The skill requires the Power BI Modeling MCP Server to connect to and modify semantic models. Without it, you can only receive general guidance without analyzing your specific model structure.
Yes. The skill provides DAX measure guidance and can create measures with proper syntax, naming conventions, and documentation. Reference MEASURES-DAX.md for detailed DAX patterns and best practices.
Yes. The skill supports both Power BI Desktop models and Fabric semantic models through the connection_operations tool (Connect, ConnectFabric).
It uses a best practices checklist covering star schema design, naming conventions, documentation, relationships, hidden fields, and explicit measures. It compares your model against these standards and recommends improvements.
Yes. The skill can create and configure RLS roles using security_role_operations, restricting data access based on user identity. See RLS.md for implementation patterns.
Full instructions (SKILL.md)
Source of truth, from github/awesome-copilot.
name: powerbi-modeling description: 'Power BI semantic modeling assistant for building optimized data models. Use when working with Power BI semantic models, creating measures, designing star schemas, configuring relationships, implementing RLS, or optimizing model performance. Triggers on queries about DAX calculations, table relationships, dimension/fact table design, naming conventions, model documentation, cardinality, cross-filter direction, calculation groups, and data model best practices. Always connects to the active model first using power-bi-modeling MCP tools to understand the data structure before providing guidance.'
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"
Prerequisites
Required Tools
- Power BI Modeling MCP Server: Required for connecting to and modifying semantic models
- Enables: connection_operations, table_operations, measure_operations, relationship_operations, etc.
- Must be configured and running to interact with models
Optional Dependencies
- Microsoft Learn MCP Server: Recommended for researching latest best practices
- Enables: microsoft_docs_search, microsoft_docs_fetch
- Use for complex scenarios, new features, and official documentation
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
Related skills
More from github/awesome-copilot and the wider catalog.
git-commit
Execute semantic git commits with conventional message analysis and intelligent staging.
excalidraw-diagram-generator
Generate Excalidraw diagrams from natural language descriptions.
documentation-writer
Create structured technical documentation using the Diátaxis framework for tutorials, how-to guides, references, and explanations.
gh-cli
GitHub CLI comprehensive reference for repositories, issues, PRs, Actions, projects, releases, and all GitHub operations from the command line.
prd
Generate comprehensive Product Requirements Documents with executive summaries, user stories, technical specs, and risk analysis.
refactor
Surgical code refactoring to improve maintainability without changing behavior.