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