Relationships connect your fact tables to attribute tables, enabling powerful filtering, grouping, and cross-dimensional analysis. This guide covers how to establish relationships, understand star schema design, and troubleshoot common relationship issues.
Why Relationships Matter
Without relationships, your fact and attribute tables are isolated islands of data. Relationships create bridges between them, enabling you to:
Select "Northeast Region" and see only matching transactions
Sum sales by customer segment or product category
Display customer names instead of just IDs
Understanding Star Schema
Smartload uses a star schema design—a central fact table surrounded by attribute tables, like points of a star. This is the industry-standard approach for analytical data models.
The fact table sits at the center, connected to multiple attribute tables via relationships.
Creating Relationships
To establish a relationship between tables:
Open Your Fact Table
Click on the fact table tile, then look for the Relationships or Link option.
Select the Foreign Key Column
Choose the column in your fact table that contains the lookup values (e.g., CustomerID).
Choose the Attribute Table
Select which attribute table to link to (e.g., Customer Master).
Map the Primary Key
Select the matching primary key column in the attribute table. Process to activate.
Relationship Types
Smartload primarily uses many-to-one relationships—many fact rows can reference one attribute row.
Troubleshooting Common Issues
Next Steps
With your data model complete, you can now add sophisticated calculations using DAX formulas.
Relationships are the foundation of a well-designed analytical model. Take time to ensure your keys are clean and unique, and your star schema will reward you with fast, flexible analysis. When issues arise, check for duplicate keys first— they're the most common culprit.
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