The answer is to reduce the number of columns in the Customer dimension by removing unused columns. This is the correct first step because high-cardinality dimensions, like Customer with 100,000 rows, consume significant memory; removing unnecessary columns (e.g., address details) directly reduces model size and speeds up filter operations across multiple categories and regions. On the PL-300 exam, this tests your understanding that column cardinality and storage impact performance more than minor tweaks like disabling auto date/time, which is a common trap. A frequent mistake is jumping to aggregations or storage mode changes, but the simplest, most impactful optimization is trimming unused columns from large tables. Memory tip: "Trim the fat, not the data" — always audit high-row-count tables for redundant columns first.
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 a Power BI developer at a retail company. You have a data model with a 'Sales' fact table (10 million rows) and dimension tables: 'Date', 'Customer', 'Product', 'Store'. The 'Sales' table includes columns: SalesID, DateKey, CustomerID, ProductID, StoreID, Quantity, UnitPrice, Discount, TotalAmount. The 'Product' dimension has 5,000 rows and includes columns: ProductID, ProductName, Category, SubCategory, Brand, Price. The 'Store' dimension has 200 rows and includes columns: StoreID, StoreName, Region, City, Manager. The 'Customer' dimension has 100,000 rows. The report currently has a measure 'Total Sales' = SUM(Sales[TotalAmount]) and a measure 'Total Quantity' = SUM(Sales[Quantity]). Users complain that the report is slow when filtering by multiple categories and regions simultaneously. You need to improve performance without changing the data source. Which action should you take first?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "first"
Why it matters: Order matters here. You are being tested on which action comes before the others — not which action is generally useful.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Reduce the number of columns in the Customer dimension by removing unused columns
Option C is correct because reducing the cardinality of the Customer dimension by removing unnecessary columns (e.g., address details) can significantly reduce model size and improve performance. Option A is wrong because disabling auto date/time might help but is a minor improvement. Option B is wrong because aggregations can help but require additional setup and are not the first step. Option D is wrong because changing to dual storage mode may not improve performance and could increase complexity.
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.
✗
Create an aggregation table for the Sales table
Why it's wrong here
Aggregations are useful but require careful design and are not the simplest first step.
✗
Disable the auto date/time feature in Power BI
Why it's wrong here
This may reduce model size slightly but is not the most impactful first step.
✗
Change the storage mode of the Sales table to Dual
Why it's wrong here
Dual mode may not improve performance if the model is already in Import mode.
✓
Reduce the number of columns in the Customer dimension by removing unused columns
Why this is correct
Removing unnecessary columns reduces model size and improves performance.
Clue confirmation
The clue word "first" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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: Reduce the number of columns in the Customer dimension by removing unused columns — Option C is correct because reducing the cardinality of the Customer dimension by removing unnecessary columns (e.g., address details) can significantly reduce model size and improve performance. Option A is wrong because disabling auto date/time might help but is a minor improvement. Option B is wrong because aggregations can help but require additional setup and are not the first step. Option D is wrong because changing to dual storage mode may not improve performance and could increase complexity.
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: "first". Order matters here. You are being tested on which action comes before the others — not which action is generally useful.
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. A company has a Power BI semantic model that uses Import mode. The model contains a table with 10 million rows. The data source is a SQL Server view that takes 5 minutes to execute. The scheduled refresh is set to every hour. What is the likely impact on refresh performance?
easy
A.Refresh will fail due to timeout on the gateway.
B.The model will automatically use incremental refresh to split the load.
C.Refresh will complete in parallel with the view execution.
✓ D.Refresh will take at least 5 minutes plus data loading time.
Why D: Option D is correct because the refresh process must first execute the SQL Server view to retrieve data, which takes at least 5 minutes, and then load that data into the Import mode model. The total refresh time is the sum of the query execution time and the data loading time, so it will be at least 5 minutes plus additional time for loading 10 million rows.
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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.
Question Discussion
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