Introduction
In Power BI, Data modelling is the process of creating visual representations of the relationships between data structures, including information about the individual attributes within those structures. These visual representations are referred to as schemas.
2 main schemas are employed in Power BI, and they are: Star and Snowflake.
In Power BI, schemas can be found under the fields/data pane, located on the right-hand side of the Power BI window, under model view.
The star schema
A star schema is one where a single fact table is surrounded by multiple-dimension tables. The fact table contains the numeric measures or facts of the data model, while the dimension tables contain descriptive attributes or dimensions of the data model. Just as the name suggests, the visual resembles a star⭐
The Snowflake schema
On the other hand, a snowflake schema is a type of schema that extends the star schema by normalizing dimension tables. In other words, one central fact table connects to multiple dimension tables, but one or more of those dimension tables are further divided into multiple related sub-dimension tables.
This ultimately results in a structure that resembles a snowflake❄️
Relationships in Star and Snowflake Schemas
How fact tables and dimension tables connect is what is defined as a relationship. They are basically defined by the use of Primary Keys(PK) and Foreign Keys(FK).
PK : A unique identifier for every row in a table
FK : A column in one table that references the Primary Key of another table, creating a link between them.
Importance of Good Data Modelling Practices for Performance and Accurate Reporting
| Performance | Reporting |
|---|---|
| Optimized query speed | Single source of truth |
| Reduced complexity and resource usage | Data integrity |
| scalability | contextual understanding |
| Faster processing | Fewer errors |
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