Data Modelling And Schemas in Power Bi,Relationships and clarification:Beginner.

Source: Dev.to

What is Data Modelling

• Data modelling is the process of organizing tables and defining relationships between them so Power BI can understand how data connects.
• It works like a map of connections:
  • Tables = locations where data is stored.
  • Relationships = roads connecting the tables.
  • DAX calculations = directions that rely on the roads being correct.

Benefits of a Good Model

• Accurate calculations
• Better performance
• Easier report building
• Scalability for large datasets

What is a Schema in Power BI

• A schema describes the structure of your data model—how tables are arranged and connected.

Power BI Schemas

Power BI typically follows data‑warehouse schemas, mainly:

1. Star schema
2. Snowflake schema
3. Flat table (single table)

Star Schema

The star schema is the most recommended structure in Power BI.

Structure

• Fact Table (center)
• Dimension Tables (around it)

Fact Table Example

Dimension Tables

• Products (ProductId, ProductName, Category)
• Customers (CustomerID, CustomerName, Region)
• Date (DateID, Year, Month, Day)

Importance

• Simple relationships
• Faster performance
• Easier DAX calculations
• Clear visuals

Snowflake Schema

The snowflake schema is a more normalized version of the star schema.

Structure

• Dimensions are split into multiple related tables (e.g., product → categories → subcategories).
• Reduces data duplication.
• Useful for complex hierarchies.

Cardinality

• Describes how rows match between tables.
• One‑to‑many (1:*) – e.g., one customer → many sales.
• One‑to‑one – rare.
• Many‑to‑many (*) – avoid if possible.

Filter Direction (Important)

• Single Direction – filter flow from dimension to fact table, preventing ambiguity.