PL-300 Prepare the data Practice Question
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?
⚠ Common exam trap
Many exam-takers 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.
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
✓
Define aggregations in Power BI on the DirectQuery tables.
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.
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
Creating a composite model with an imported aggregated table introduces a separate refresh cycle for that table, so the aggregated data may become stale relative to the DirectQuery source. While composite models can mix storage modes, the imported portion still adds import latency and synchronization overhead, which does not address the need for real-time performance on large DirectQuery tables.
- ✓
Define aggregations in Power BI on the DirectQuery tables.
Why this is correct
Defining aggregations in Power BI on the DirectQuery tables is correct because Power BI can automatically redirect queries to a cached aggregation table when the query grain matches, drastically reducing load on the source and improving response times. This approach maintains the DirectQuery storage mode for detail-level queries, so users still see fresh data without a full import, and it leverages Power BI's optimization engine rather than requiring source-side changes.
- ✗
Change the storage mode to Import for the fact table.
Why it's wrong here
Changing the storage mode to Import for the fact table would convert all data into an in-memory cache, which introduces a refresh latency that could easily exceed the 15-minute requirement. Large fact tables also consume significant memory and require frequent full or incremental refreshes, making near-real-time reporting impractical and potentially causing resource contention with other workloads.
- ✗
Create a SQL Server view that aggregates data and use it as the source.
Why it's wrong here
Creating a SQL Server view that aggregates data pushes some work to the source database, but it forces all Power BI queries to use that pre-aggregated view, stripping away the ability to access detailed records or let Power BI dynamically choose between aggregated and detail levels. The view itself still uses DirectQuery, so performance depends on the source engine's optimization, and it does not leverage Power BI's built-in aggregation capabilities or query caching.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.