Creating dimension tables vs filtering based on columns within the fact table

Hi Anon1234 ,

(a)One approach is to ensure that each dimension table has a unique key for each row. You can replace null values with a placeholder value (e.g., "Unknown") to maintain the integrity of the relationships.

Understand star schema and the importance for Power BI - Power BI | Microsoft Learn

(b)Single-Column Dimension Tables: While technically possible, this is not recommended as it can lead to a fragmented and inefficient model. Dimension tables should ideally contain multiple related attributes that describe the entities in your fact table.

Power BI Basics of Modeling: Star Schema and How to Build it - RADACAD

(c)Keeping everything in one table (except for dates) can simplify the model but may lead to performance issues and difficulties in managing and updating the data. The star schema is designed to optimize performance and usability by separating descriptive attributes into dimension tables.

Build Your First Star Schema Model in Action: Power BI Modeling Basics - RADACAD

(d)Something else:

Flatten Dimension Tables; Ensure Unique Keys; 

Best Regards,

Neeko Tang

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