Quick Answer
The correct columns to move to dimension tables are ProductID, ProductName, Category, and SubCategory. In a star schema, dimension tables store descriptive attributes that provide context for the numeric measures in the fact table, while the fact table holds the quantitative data used for aggregation. Here, ProductID, ProductName, Category, and SubCategory are all descriptive fields that enable efficient filtering, grouping, and slicing in Power BI, whereas Price and Cost are numeric values that should remain in the fact table as additive or semi-additive measures. On the PL-300 exam, this tests your understanding of star schema design principles, often appearing in case studies where you must distinguish between dimension attributes and fact measures. A common trap is moving Price or Cost to the dimension table, thinking they are attributes, but they are actually measures used in calculations like total revenue or profit margin. Memory tip: think “descriptive goes to dimensions, numbers go to facts”—if it describes what you’re measuring, it belongs in a dimension.
This PL-300 practice question tests your understanding of prepare the data. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
You are preparing data for a sales analysis report. The source system provides a table with columns: 'ProductID', 'ProductName', 'Category', 'SubCategory', 'Price', 'Cost'. You need to create a star schema. Which columns should be moved to dimension tables?
ProductID, ProductName, Category, and SubCategory
These are all attributes of the product.
ProductID and ProductName only
Why wrong: Category and SubCategory should also be in the dimension.
Price and Cost
Why wrong: These are numeric measures, not dimension attributes.
ProductID, ProductName, Price, and Cost
Why wrong: Price and Cost should remain in the fact table.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
ProductID, ProductName, Category, and SubCategory
In a star schema, dimension tables contain descriptive attributes that provide context to measures. ProductID, ProductName, Category, and SubCategory are all descriptive attributes that should be moved to a dimension table (e.g., DimProduct) to reduce redundancy and enable efficient filtering and grouping. Measures like Price and Cost, however, are numeric values that typically belong in the fact table as additive or semi-additive measures.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
ProductID, ProductName, Category, and SubCategory
Why this is correct
These are all attributes of the product.
Related concept
Read the scenario before looking for a memorised answer.
ProductID and ProductName only
Why it's wrong here
Category and SubCategory should also be in the dimension.
Price and Cost
Why it's wrong here
These are numeric measures, not dimension attributes.
ProductID, ProductName, Price, and Cost
Why it's wrong here
Price and Cost should remain in the fact table.
Common exam traps
The trap here is that candidates often confuse numeric columns like Price and Cost as dimensions because they are static per product, but in a star schema, any column that is a measure (aggregatable numeric value) belongs in the fact table, not the dimension table.
Detailed technical explanation
In Power BI, star schema design optimizes query performance by reducing the number of joins and enabling columnstore index compression on fact tables. Moving descriptive columns like Category and SubCategory to a dimension table allows for role-playing dimensions and supports bi-directional cross-filtering without data duplication. A real-world scenario is when you need to analyze sales by multiple product hierarchies; having these attributes in a dimension table ensures consistent filtering across different fact tables (e.g., Sales, Inventory).
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
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FAQ
Prepare the data — This question tests Prepare the data — Read the scenario before looking for a memorised answer..
The correct answer is: ProductID, ProductName, Category, and SubCategory — In a star schema, dimension tables contain descriptive attributes that provide context to measures. ProductID, ProductName, Category, and SubCategory are all descriptive attributes that should be moved to a dimension table (e.g., DimProduct) to reduce redundancy and enable efficient filtering and grouping. Measures like Price and Cost, however, are numeric values that typically belong in the fact table as additive or semi-additive measures.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
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