The correct approach is to define aggregations in Power BI on the DirectQuery tables. This works because Power BI’s aggregation management feature allows you to map queries to pre-aggregated tables—such as indexed views or materialized views in SQL Server—so the engine can transparently route high-level queries to the smaller, faster aggregated data while still fetching granular details from the source when needed. On the PL-300 exam, this scenario tests your understanding of how to balance near real-time latency with performance, a common challenge when using DirectQuery with massive fact tables. A frequent trap is assuming you must switch to Import mode or create aggregations only in the source; instead, Power BI’s in-model aggregation definitions let you leverage source-side aggregations without breaking the 15-minute freshness requirement. Memory tip: think of aggregations as a “smart shortcut” for the query engine—it takes the fast lane to pre-summarized data whenever possible.
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 a data analyst for a multinational corporation. You are building a Power BI report that uses a large fact table (100 million rows) and several dimension tables. The data source is a SQL Server data warehouse. Users need to see near real-time data with a maximum latency of 15 minutes. The current import mode takes too long to refresh. You decide to use DirectQuery mode. However, queries are slow. You need to improve query performance. You consider creating aggregations in the data source. Which approach should you take in Power BI to leverage these aggregations?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Define aggregations in Power BI on the DirectQuery tables.
Option B is correct because Power BI allows you to define aggregations on DirectQuery tables, which enables the engine to route queries to pre-aggregated data at the source (e.g., SQL Server indexed views or materialized views) when possible, significantly reducing query latency. This approach leverages the existing aggregations in the data source without changing the storage mode or importing data, maintaining near real-time freshness with a 15-minute latency requirement.
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 a composite model with an imported aggregated table.
Why it's wrong here
This adds import latency.
✓
Define aggregations in Power BI on the DirectQuery tables.
Why this is correct
Power BI can use these aggregations for faster queries.
Related concept
Read the scenario before looking for a memorised answer.
✗
Change the storage mode to Import for the fact table.
Why it's wrong here
Increases latency beyond 15 minutes.
✗
Create a SQL Server view that aggregates data and use it as the source.
Why it's wrong here
This moves aggregation to source, but Power BI can also do it.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often think creating a SQL Server view (Option D) is the correct Power BI approach, but Power BI cannot automatically leverage such views as aggregations unless they are explicitly defined in the model; the exam tests whether you know that aggregations must be defined within Power BI on DirectQuery tables to enable query rewriting.
Detailed technical explanation
How to think about this question
Power BI aggregations work by creating a mapping between a detailed DirectQuery table and an aggregated table (either imported or also DirectQuery), allowing the engine to automatically rewrite queries to use the aggregation when the granularity matches. Under the hood, Power BI sends a query to the source that matches the aggregation table's grain, reducing data movement and compute overhead; for example, if the source has a daily sales aggregation, Power BI can answer a monthly report query from that aggregation instead of scanning 100 million rows. In real-world scenarios, this is critical for large fact tables in SQL Server data warehouses where indexed views or materialized views exist, as Power BI can leverage them without manual query routing.
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 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 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: Define aggregations in Power BI on the DirectQuery tables. — Option B is correct because Power BI allows you to define aggregations on DirectQuery tables, which enables the engine to route queries to pre-aggregated data at the source (e.g., SQL Server indexed views or materialized views) when possible, significantly reducing query latency. This approach leverages the existing aggregations in the data source without changing the storage mode or importing data, maintaining near real-time freshness with a 15-minute latency requirement.
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.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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