DA0-002 Data Analysis Practice Question
A data analyst is designing a data model for a sales data warehouse. The model should optimize query performance for aggregations by minimizing joins and duplicating data where necessary. Which schema design should the analyst use?
⚠ Common exam trap
DA0-002 often tests the misconception that normalization always improves performance, but in data warehousing, denormalization via star schema is preferred for analytical query speed.
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
✓
Star schema
A star schema is the correct choice because it organizes data into a central fact table surrounded by denormalized dimension tables, which minimizes the number of joins required for aggregation queries. By duplicating dimension attributes rather than normalizing them, the star schema trades storage for query speed, making it ideal for data warehouse workloads that emphasize analytical performance. This design directly supports the requirement to optimize aggregations while reducing join complexity.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Entity-relationship model
Why it's wrong here
An entity-relationship model is a conceptual design artefact, not a physical warehouse schema, so it defines no fact or dimension tables to aggregate against. It is tempting because it precedes dimensional modelling, and it would be correct during requirements gathering, before choosing a star schema for the warehouse.
- ✗
Snowflake schema
Why it's wrong here
Snowflake schema normalises dimensions into multiple related tables, adding joins that the stem explicitly asks to minimise. It is tempting because it reduces storage redundancy, and it would be correct where dimension storage or update consistency outweighs aggregation speed, unlike this performance-focused warehouse.
- ✗
3NF normalized model
Why it's wrong here
A 3NF model spreads attributes across many tables, so aggregation queries require numerous joins, contradicting the requirement to minimise joins. It is tempting because 3NF reduces redundancy and suits transactional systems, but the star schema's denormalised dimensions and fact table are what optimise analytical aggregation performance.
- ✓
Star schema
Why this is correct
A star schema places a central fact table surrounded by denormalised dimension tables, so aggregation queries join fewer tables and scan pre-joined data. This deliberately duplicates attributes to minimise joins, matching the stated performance requirement.
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Last reviewed September 2026 · checked against the official CompTIA exam blueprint
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.