The answer is to design a star schema with a fact table and dimension tables. This modeling approach delivers the best query performance for a Sales table with over 100 million rows because it separates transactional data (facts) from descriptive attributes (dimensions), drastically reducing table scans and enabling efficient aggregations and compression in Power BI. On the PL-300 exam, this question tests your understanding of dimensional modeling trade-offs: a single flat table causes bloated storage and slow queries, a snowflake schema introduces unnecessary joins that degrade performance, and importing all data into one table duplicates information and loses normalization benefits. The exam often presents these as distractors, so remember that star schemas are the gold standard for self-service analytics because they balance speed with user-friendliness. Memory tip: think of a star as a central fact table with dimension tables radiating outward like points—keep it flat, keep it fast.
PL-300 Model the data Practice Question
This PL-300 practice question tests your understanding of model the data. 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.
You are designing a data model that will support self-service analytics. You have a Sales table with over 100 million rows. Which of the following modeling approaches would provide the best query performance while maintaining a user-friendly experience?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "best"
Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Design a star schema with a fact table and dimension tables
Star schema design separates facts and dimensions, optimizing query performance by reducing table scans and enabling efficient aggregations. Option C is correct. Option A is wrong because a single flat table with many columns can cause performance issues and is harder to maintain. Option B is wrong because a snowflake schema can increase query complexity and reduce performance due to additional joins. Option D is wrong because importing all tables into a single table duplicates data and loses normalization benefits.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✓
Design a star schema with a fact table and dimension tables
Why this is correct
Star schema is optimized for Power BI.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Create a single flat table with all columns
Why it's wrong here
Flat tables cause poor performance and redundancy.
✗
Import all tables into a single table using Power Query merge
Why it's wrong here
Merging into one table defeats the purpose of modeling.
✗
Use a snowflake schema with multiple levels of dimensions
Why it's wrong here
Snowflake can degrade performance due to many joins.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which PL-300 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Model the data — This question tests Model the data — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Design a star schema with a fact table and dimension tables — Star schema design separates facts and dimensions, optimizing query performance by reducing table scans and enabling efficient aggregations. Option C is correct. Option A is wrong because a single flat table with many columns can cause performance issues and is harder to maintain. Option B is wrong because a snowflake schema can increase query complexity and reduce performance due to additional joins. Option D is wrong because importing all tables into a single table duplicates data and loses normalization benefits.
What should I do if I get this PL-300 question wrong?
Identify which PL-300 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Are there clue words in this question I should notice?
Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
What is the key concept behind this question?
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 →
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. You are designing a data model for a report that shows sales by product category and by month. Which table configuration is most efficient?
medium
A.Two fact tables: one for date and one for product.
✓ B.A date dimension table, a product dimension table, and a sales fact table.
C.A single table with all columns.
D.One dimension table containing date and product attributes.
Why B: Option D is correct because a star schema with separate tables for date and product is the most efficient for filtering and performance. Option A is wrong because combining date and product into one dimension is not needed. Option B is wrong because a single table is inefficient. Option C is wrong because a bridge table is not needed for a simple star schema.
Variation 2. You are designing a data model for a report that shows sales by region and product category. The source data includes a table 'Sales' with columns: Region, Category, SalesAmount. You also have separate tables 'Regions' and 'Categories' that contain additional attributes. You need to create a star schema. What should you do with the 'Region' and 'Category' columns in the 'Sales' table?
medium
✓ A.Remove them from the Sales table and use foreign keys to link to the dimension tables
B.Keep them in the Sales table as attributes for simplicity
C.Merge the Regions and Categories tables into the Sales table
D.Mark the Sales table as a date table
Why A: Option C is correct because in a star schema, dimension tables contain the attributes, and fact tables contain foreign keys. Removing the columns and using foreign keys normalizes the model. Option A is wrong because keeping them duplicates data and increases model size. Option B is wrong because merging them is not necessary and can complicate the model. Option D is wrong because marking as date tables is irrelevant for region and category.
Variation 3. You are designing a star schema for a sales data model. Which table should be defined as a dimension table?
medium
A.TransactionID
B.OrderQuantity
C.SalesAmount
✓ D.Date
Why D: Option B is correct because Date is a classic dimension used for time-based analysis. Option A is wrong because SalesAmount is a measure. Option C is wrong because TransactionID is a fact table key. Option D is wrong because OrderQuantity is a measure.
Last reviewed: Jun 21, 2026
Question Discussion
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This PL-300 practice question is part of Courseiva's free Microsoft 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 PL-300 exam.
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