Powerbi-Modeling

# 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](references/STAR-SCHEMA.md)

- Relationship configuration: See [RELATIONSHIPS.md](references/RELATIONSHIPS.md)

- DAX measures and naming: See [MEASURES-DAX.md](references/MEASURES-DAX.md)

- Performance optimization: See [PERFORMANCE.md](references/PERFORMANCE.md)

- Row-level security: See [RLS.md](references/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_operation