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
A Vault schema is a Data Vault construct of hubs, links and satellites for auditable, insert-only integration layers, not normalised dimensional tables. It is tempting when historised, source-agnostic loading is required, but the stem describes normalising product, customer and time dimensions within a dimensional model, which yields a snowflake schema.
- ✗
Star schema
Why it's wrong here
A Star schema keeps each dimension as one denormalised table directly joined to the fact table, so redundancy remains rather than being reduced. It is tempting as the default dimensional design for fast, simple querying, but the stem explicitly normalises dimensions into multiple related tables, producing a snowflake schema.
- ✗
Galaxy schema
Why it's wrong here
A Galaxy schema comprises multiple fact tables sharing conformed dimensions; it does not normalise a single fact table's dimensions into related tables. It is tempting when several business processes must be analysed together, but the stem concerns one sales fact table with normalised dimensions, which is a snowflake schema.
- ✓
Snowflake schema
Why this is correct
Normalising dimensions into multiple related tables produces a snowflake schema: each dimension is decomposed into its own hierarchy of linked tables rather than one flat denormalised table. This directly satisfies the stated goal of reducing redundancy in the product, customer and time dimensions.
About these practice questions
Courseiva writes every DA0-002 question from scratch — 1,004 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DA0-002 practice question is part of Courseiva's free CompTIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DA0-002 exam.