PL-300 Model the data Practice Question
You are creating a star schema in Power BI. Which TWO tables are typically dimension tables?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Product
In a star schema, dimension tables hold descriptive attributes used to slice and filter facts, so B (Product) is correct because it stores descriptive product attributes like name, category, and subcategory that relate to fact tables. C (Date) is also correct because a date/calendar table provides time attributes (year, quarter, month, day) for time intelligence and filtering, making it a classic dimension. By contrast, A (TransactionDetails), D (InventoryTransactions), and E (Sales) are transactional or event-level tables that store measures and foreign keys, so they are fact tables rather than dimensions.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
TransactionDetails
Why it's wrong here
TransactionDetails is a fact table, not a dimension table. It records granular business events—such as line-item-level transactions—with numeric measures (e.g., quantity, price) and foreign keys pointing to dimension tables. In a star schema, dimensions hold descriptive attributes for filtering, while facts hold measures; placing transactional detail in the dimension layer violates this separation of concerns.
- ✓
Product
Why this is correct
Product is a classic dimension table. It contains descriptive attributes like product key, name, category, subcategory, color, and size, and is related to fact tables through a one-to-many relationship. Because it provides the contextual attributes used for slicing and grouping transactional data, Product belongs in the dimension layer, not the fact layer, and is correctly selected here.
- ✓
Date
Why this is correct
Date is a standard role-playing dimension in a star schema. It provides a continuous calendar hierarchy (year, quarter, month, day) and is joined to fact tables using a date foreign key, enabling time-based filtering and time-intelligence calculations. Even though dates appear in many tables, modeling Date as a separate dimension table ensures consistent time analysis and is required for proper Power BI date logic.
- ✗
InventoryTransactions
Why it's wrong here
InventoryTransactions is a fact table that captures transactional inventory movements, including receipts, issues, adjustments, quantities, and unit costs. It stores measurable data and references dimension keys, which is the defining characteristic of a fact table. Treating it as a dimension would improperly place measures in the lookup layer, breaking the star schema's normalization of descriptive attributes.
- ✗
Sales
Why it's wrong here
Sales is a fact table containing transactional measures such as revenue, quantity sold, and unit price, along with foreign keys linking to Customer, Product, Date, and Store dimensions. In a star schema, fact tables are the 'many' side of relationships and are never treated as dimension tables. Using Sales as a dimension would mix measures with descriptive attributes, causing aggregation errors and poor model design.
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