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