The correct choice is to ensure each dimension table has a unique key and contains descriptive attributes. This is a fundamental best practice in a star schema because dimension tables are designed to be denormalized, meaning they consolidate all descriptive attributes into a single table per business entity, allowing for efficient filtering, grouping, and slicing of the fact table’s numeric measures. On the Microsoft Power BI Data Analyst PL-300 exam, this concept tests your understanding of dimensional modeling fundamentals, often appearing in scenario-based questions where you must choose between a normalized snowflake schema and a denormalized star schema. A common trap is selecting an option that suggests splitting attributes across multiple related tables, which violates the denormalized dimension best practice and can degrade query performance. Remember the memory tip: “Dimensions describe, facts measure—keep your descriptions together in one unique-keyed table.”
PL-300 Prepare the data Practice Question
This PL-300 practice question tests your understanding of prepare 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 preparing data from multiple sources for a Power BI report. You need to create a star schema with a single fact table and several dimension tables. Which of the following is a best practice when designing the data model?
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
✓
Ensure each dimension table has a unique key and contains descriptive attributes.
In a star schema, dimension tables should have a unique key (surrogate or natural) and contain descriptive attributes to enable filtering and grouping in Power BI. This ensures efficient relationships with the fact table and supports intuitive report interactions. Option C directly aligns with this best practice.
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.
✗
Include calculated measures in dimension tables.
Why it's wrong here
Measures belong in fact tables or as separate calculated columns; dimension tables should contain only attributes.
✗
Normalize dimension tables into multiple related tables.
Why it's wrong here
Snowflake schemas can complicate reporting; denormalized dimensions are preferred for simplicity and performance.
✓
Ensure each dimension table has a unique key and contains descriptive attributes.
Why this is correct
This is a fundamental best practice for star schema design.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Use natural keys from the source system as the primary key in dimension tables.
Why it's wrong here
Natural keys can change; surrogate keys are more stable and recommended in data warehouses.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Microsoft often tests the misconception that normalizing dimension tables (snowflake schema) is a best practice for performance, but in Power BI, denormalized star schemas are preferred to reduce joins and leverage VertiPaq compression.
Detailed technical explanation
How to think about this question
Power BI's VertiPaq engine compresses dimension tables more efficiently when they have a single unique key and are denormalized, reducing memory usage and improving query speed. Using surrogate keys (e.g., integer identity columns) avoids issues with source system key changes, such as when a natural key is reused or updated, which would break relationships in the model. In real-world scenarios, dimension tables like 'Customer' often include attributes like name, region, and segment, all stored in one table to minimize join complexity and optimize DAX filter propagation.
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.
TExam Day Tips
→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 exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Prepare the data — This question tests Prepare the data — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Ensure each dimension table has a unique key and contains descriptive attributes. — In a star schema, dimension tables should have a unique key (surrogate or natural) and contain descriptive attributes to enable filtering and grouping in Power BI. This ensures efficient relationships with the fact table and supports intuitive report interactions. Option C directly aligns with this best practice.
What should I do if I get this PL-300 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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
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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 preparing data for a star schema. Which THREE types of tables are typically included in a star schema?
medium
A.Staging tables
B.Bridge tables
✓ C.Dimension tables
✓ D.Date tables
✓ E.Fact tables
Why C: In a star schema, dimension tables (C) provide descriptive attributes for the measures stored in fact tables. They are denormalized to optimize query performance in tools like Power BI, enabling fast slicing and dicing of data without complex joins.
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Question Discussion
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