DA0-002 Data Concepts and Environments Practice Question
A data modeler is designing a dimensional model for a sales analytics system. The fact table contains sales transactions, and the dimension tables include product, customer, and time. To reduce data redundancy, the modeler normalizes the dimension tables into multiple related tables. Which schema is being implemented?
⚠ Common exam trap
CompTIA often tests the distinction between star and snowflake schemas by emphasizing normalization of dimensions; the trap here is that candidates may confuse 'normalized dimensions' with a star schema, which actually uses denormalized dimensions for simplicity and performance.
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
✓
Snowflake schema
The snowflake schema is a dimensional model where dimension tables are normalized into multiple related tables to reduce data redundancy. In this scenario, the product, customer, and time dimensions are split into sub-dimensions (e.g., product category, customer geography, time hierarchy), which is the defining characteristic of a snowflake schema. This contrasts with a star schema where dimensions remain denormalized.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Vault schema
Why it's wrong here
Vault schema is a different approach focusing on hubs, links, and satellites.
- ✗
Star schema
Why it's wrong here
Star schema has denormalized dimension tables, not normalized.
- ✗
Galaxy schema
Why it's wrong here
Galaxy schema contains multiple fact tables sharing dimensions.
- ✓
Snowflake schema
Why this is correct
Snowflake schema normalizes dimension tables to reduce redundancy.
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