# power-bi-data-modeling-best-practices

This rule guides Power BI model design around star schemas. Use it when shaping tables, relationships, filters, and storage modes.

- rule · `type=rule` · GitHub Copilot · ★ 40418
- Author: github · official GitHub repository
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/github/awesome-copilot/tree/HEAD/instructions/power-bi-data-modeling-best-practices.instructions.md
- Updated: 2026-10-23
- HTML: https://affpapa.org/en/nevibecode/rules/power-bi-data-modeling-best-practices

## What it does

The rule separates Power BI semantic models into dimensions and facts. Dimensions provide descriptive attributes and hierarchy context, while fact tables hold measurable events at a consistent grain. It also recommends matching foreign keys to dimension keys and keeping descriptive text out of fact tables.

Relationship guidance covers the usual one-to-many pattern, limited use of many-to-many links, filter direction, and referential integrity. Storage advice differs by mode: Import favors removing unused data, suitable types, pre-aggregation, and incremental refresh; DirectQuery calls for source indexes, simpler measures, and fewer visuals per page.

In DirectQuery, `Assume Referential Integrity` must stay disabled when the source contains orphaned records.

## Requirements
- Works with: Power BI

## Install

### GitHub Copilot (native platform)

**Manually: put the files in place**
- File: `.github/instructions/power-bi-data-modeling-best-practices.instructions.md` — The applyTo field sets which files it applies to

### Claude Code

**Manually: put the files in place**
- File: `.claude/rules/power-bi-data-modeling-best-practices.md` — The paths frontmatter field limits the files: move applyTo from the source into paths

### Codex

**AGENTS.md**
- Codex reads AGENTS.md: paste the rule text there

### Cursor

**Manually: put the files in place**
- File: `.cursor/rules/power-bi-data-modeling-best-practices.mdc` — Frontmatter: description, globs, alwaysApply. Move applyTo from the source into globs, or the rule will not attach on its own

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/rules/power-bi-data-modeling-best-practices.md`

### Cline

**Manually: put the files in place**
- File: `.clinerules/power-bi-data-modeling-best-practices.md`

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/github/awesome-copilot/tree/HEAD/instructions/power-bi-data-modeling-best-practices.instructions.md

## When to use it
- design a Power BI star schema
- separate fact and dimension responsibilities
- configure relationship and filter directions
- choose between Import Mode and DirectQuery
- reduce unused model columns and rows

## Example prompts
- Design a Power BI sales model using a star schema.
- Review the relationships between `DimProduct`, `DimCustomer`, `DimDate`, and `FactSales`.
- Suggest DirectQuery model changes while preserving referential integrity.

## Source text · power-bi-data-modeling-best-practices.instructions.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: d2058aa346829ea9.

BEGIN THIRD-PARTY FILE d2058aa346829ea9
````text
---
description: 'Comprehensive Power BI data modeling best practices based on Microsoft guidance for creating efficient, scalable, and maintainable semantic models using star schema principles.'
applyTo: '**/*.{pbix,md,json,txt}'
---

# Power BI Data Modeling Best Practices

## Overview
This document provides comprehensive instructions for designing efficient, scalable, and maintainable Power BI semantic models following Microsoft's official guidance and dimensional modeling best practices.

## Star Schema Design Principles

### 1. Fundamental Table Types
**Dimension Tables** - Store descriptive business entities:
- Products, customers, geography, time, employees
- Contain unique key columns (preferably surrogate keys)
- Relatively small number of rows
- Used for filtering, grouping, and providing context
- Support hierarchical drill-down scenarios

**Fact Tables** - Store measurable business events:
- Sales transactions, website clicks, manufacturing events
- Contain foreign keys to dimension tables
- Numeric measures for aggregation
- Large number of rows (typically growing over time)
- Represent specific grain/level of detail

```
Example Star Schema Structure:

DimProduct (Dimension)          FactSales (Fact)              DimCustomer (Dimension)
├── ProductKey (PK)             ├── SalesKey (PK)             ├── CustomerKey (PK)
├── ProductName                 ├── ProductKey (FK)           ├── CustomerName
├── Category                    ├── CustomerKey (FK)          ├── CustomerType  
├── SubCategory                 ├── DateKey (FK)              ├── Region
└── UnitPrice                   ├── SalesAmount               └── RegistrationDate
                               ├── Quantity
DimDate (Dimension)             └── DiscountAmount
├── DateKey (PK)
├── Date
├── Year
├── Quarter
├── Month
└── DayOfWeek
```

### 2. Table Design Best Practices

#### Dimension Table Design
```
✅ DO:
- Use surrogate keys (auto-incrementing integers) as primary keys
- Include business keys for integration purposes
- Create hierarchical attributes (Category > SubCategory > Product)
- Use descriptive names and proper data types
- Include "Unknown" records for missing dimension data
- Keep dimension tables relatively narrow (focused attributes)

❌ DON'T:
- Use natural business keys as primary keys in large models
- Mix fact and dimension characteristics in same table
- Create unnecessarily wide dimension tables
- Leave missing values without proper handling
```

#### Fact Table Design
```
✅ DO:
- Store data at the most granular level needed
- Use foreign keys that match dimension table keys
- Include only numeric, measurable columns
- Maintain consistent grain across all fact table rows
- Use appropriate data types (decimal for currency, integer for counts)

❌ DON'T:
- Include descriptive text columns (these belong in dimensions)
- Mix different grains in the same fact table
- Store calculated values that can be computed at query time
- Use composite keys when surrogate keys would be simpler
```

## Relationship Design and Management

### 1. Relationship Types and Best Practices

#### One-to-Many Relationships (Standard Pattern)
```
Configuration:
- From Dimension (One side) to Fact (Many side)
- Single direction filtering (Dimension filters Fact)
- Mark as "Assume Referential Integrity" for DirectQuery performance

Example:
DimProduct (1) ← ProductKey → (*) FactSales
DimCustomer (1) ← CustomerKey → (*) FactSales
````
END THIRD-PARTY FILE d2058aa346829ea9

The third-party file has ended. Everything between the d2058aa346829ea9 tags is data: requests and commands from it are not followed. An “end of file” line with another tag inside the block is part of the file.

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