Quick Answer
The correct answer is the snowflake schema. This schema is defined by the normalization of dimension tables into multiple related tables to reduce data redundancy, which directly addresses the scenario where product, customer, and time dimensions are split into sub-dimensions like product category or customer geography. On the CompTIA Data+ DA0-001 exam, this question tests your ability to distinguish between star and snowflake schemas in dimensional modeling, a core domain of data warehousing concepts. A common trap is confusing the snowflake schema with the star schema, but remember that the star schema keeps dimensions denormalized in a single table, while the snowflake schema breaks them apart. For a quick memory tip, think of a snowflake’s intricate, branched structure—each branch represents a normalized sub-dimension, reducing repetition just like the schema reduces redundant data.
This DA0-001 practice question tests your understanding of comparing and contrasting data concepts. 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.
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?
Vault schema
Why wrong: Vault schema is a different approach focusing on hubs, links, and satellites.
Star schema
Why wrong: Star schema has denormalized dimension tables, not normalized.
Galaxy schema
Why wrong: Galaxy schema contains multiple fact tables sharing dimensions.
Snowflake schema
Snowflake schema normalizes dimension tables to reduce redundancy.
Answer choices
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.
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.
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.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
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.
Detailed technical explanation
In a snowflake schema, normalization of dimensions (e.g., splitting 'Product' into 'Product', 'Category', and 'Supplier' tables) reduces data redundancy and storage costs but increases the number of joins required for queries, potentially degrading performance in read-heavy OLAP systems. This trade-off is often chosen when data integrity and update efficiency are prioritized over query speed, such as in slowly changing dimension (SCD) Type 2 implementations. Real-world tools like Snowflake or Redshift may optimize snowflake schemas with materialized views or query rewriting to mitigate join overhead.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A practitioner preparing for the DA0-001 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Comparing and Contrasting Data Concepts — study guide chapter
Learn the concepts, then practise the questions
Comparing and Contrasting Data Concepts practice questions
Targeted practice on this topic area only
All DA0-001 questions
509 questions across all exam domains
CompTIA Data+ DA0-001 study guide
Full concept coverage aligned to exam objectives
DA0-001 practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Practise DA0-001 questions linked to Comparing and Contrasting Data Concepts.
Practise DA0-001 questions linked to Mining and Acquiring Data.
Practise DA0-001 questions linked to Analyzing and Modeling Data.
Practise DA0-001 questions linked to Visualizing Data.
Practise DA0-001 questions linked to Communicating Data Insights.
Practise DA0-001 questions linked to CompTIA A+ hardware.
Practise DA0-001 questions linked to CompTIA A+ mobile devices.
Practise DA0-001 questions linked to CompTIA A+ networking.
Practise DA0-001 questions linked to CompTIA A+ operating systems.
Practise DA0-001 questions linked to CompTIA A+ security.
Practise DA0-001 questions linked to CompTIA A+ software troubleshooting questions.
Practise DA0-001 questions linked to CompTIA A+ operational procedures questions.
Practice this exam
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
Comparing and Contrasting Data Concepts — This question tests Comparing and Contrasting Data Concepts — Read the scenario before looking for a memorised answer..
The correct answer is: 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.
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.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Last reviewed: Jun 30, 2026
This DA0-001 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 DA0-001 exam.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.