- A
Use DirectQuery for all data sources and create views in Azure SQL to transform the SharePoint and Dataverse data. Use Power Query to combine SharePoint files in a view.
Why wrong: DirectQuery on Dataverse and SharePoint is not supported (Dataverse can be DirectQuery but SharePoint cannot). Also, using views in Azure SQL for SharePoint data would require data movement, defeating the purpose.
- B
Import all data into Power BI using Import mode. Schedule refreshes every 15 minutes for the current month and daily for historical data.
Why wrong: Import mode cannot support 15-minute refresh intervals reliably due to capacity constraints and long refresh times; also, near real-time is not achievable with scheduled import.
- C
Use a composite model: DirectQuery for the current month's sales data from Azure SQL, and Import mode for historical sales (with incremental refresh) and for customer feedback (with hourly refresh). Combine SharePoint files using Power Query and load them into the model using Import mode. Set up a DirectQuery connection for near real-time.
Composite model allows mixing storage modes; DirectQuery on the current month's data enables near real-time queries. Incremental refresh on historical data optimizes refresh. Power Query can handle SharePoint file combination.
- D
Use Azure Data Factory to copy all data to Azure SQL Database, then connect Power BI using DirectQuery.
Why wrong: While this centralizes data, it introduces batch latency and does not meet near real-time requirement unless streaming is used; also, SharePoint file combination would require additional logic.
Quick Answer
The answer is to use a composite model with DirectQuery for current-month sales and Import mode with incremental refresh for the rest. This design is correct because it directly addresses the requirement for near real-time reporting on current sales—DirectQuery queries the Azure SQL Database live, achieving under 15-minute latency—while using Import mode for historical sales and customer feedback allows scheduled daily and hourly refreshes respectively, optimizing query performance by storing those tables in memory. On the PL-300 exam, this scenario tests your understanding of composite models as a hybrid strategy, a common trap being to default to full Import or full DirectQuery, which would either miss the real-time need or degrade performance on large historical data. Remember the memory tip: “Current Direct, rest Import” to quickly recall that the most recent data uses DirectQuery for speed, while older data and smaller tables import for efficiency.
PL-300 Prepare the data Practice Question
This PL-300 practice question tests your understanding of prepare the data. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 global retail company. The company uses Power BI Premium capacity. You are building a dataset that combines sales data from three sources: 1. An Azure SQL Database that stores transactional sales data (10 million rows per day, retained for 5 years). 2. A SharePoint Online folder containing monthly Excel reports from regional offices (each report has a different structure). 3. A Dataverse table that contains customer feedback scores.
Requirements: - The dataset must support near real-time reporting for the current month's sales (maximum 15-minute latency). - Historical sales data (older than current month) can be refreshed daily. - Customer feedback scores should be updated every hour. - The Excel reports from SharePoint must be combined into a single table with consistent columns. - The final dataset should be optimized for fast query performance.
You need to design the data preparation strategy. What should you do?
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
Use a composite model: DirectQuery for the current month's sales data from Azure SQL, and Import mode for historical sales (with incremental refresh) and for customer feedback (with hourly refresh). Combine SharePoint files using Power Query and load them into the model using Import mode. Set up a DirectQuery connection for near real-time.
Option C is correct because it uses a composite model to meet all requirements: DirectQuery for near real-time current-month sales (≤15-minute latency), Import mode with incremental refresh for historical sales (daily refresh), Import mode for customer feedback (hourly refresh), and Power Query to combine SharePoint Excel files into a consistent table. This approach balances real-time needs with query performance and refresh flexibility, leveraging Power BI Premium's composite model capabilities.
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.
- ✗
Use DirectQuery for all data sources and create views in Azure SQL to transform the SharePoint and Dataverse data. Use Power Query to combine SharePoint files in a view.
Why it's wrong here
DirectQuery on Dataverse and SharePoint is not supported (Dataverse can be DirectQuery but SharePoint cannot). Also, using views in Azure SQL for SharePoint data would require data movement, defeating the purpose.
- ✗
Import all data into Power BI using Import mode. Schedule refreshes every 15 minutes for the current month and daily for historical data.
Why it's wrong here
Import mode cannot support 15-minute refresh intervals reliably due to capacity constraints and long refresh times; also, near real-time is not achievable with scheduled import.
- ✓
Use a composite model: DirectQuery for the current month's sales data from Azure SQL, and Import mode for historical sales (with incremental refresh) and for customer feedback (with hourly refresh). Combine SharePoint files using Power Query and load them into the model using Import mode. Set up a DirectQuery connection for near real-time.
Why this is correct
Composite model allows mixing storage modes; DirectQuery on the current month's data enables near real-time queries. Incremental refresh on historical data optimizes refresh. Power Query can handle SharePoint file combination.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use Azure Data Factory to copy all data to Azure SQL Database, then connect Power BI using DirectQuery.
Why it's wrong here
While this centralizes data, it introduces batch latency and does not meet near real-time requirement unless streaming is used; also, SharePoint file combination would require additional logic.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may choose Import mode for everything (Option B) without realizing the 48-refresh-per-day limit on Power BI Premium, which prevents 15-minute refreshes, or they may overlook composite models as the only way to combine real-time and historical data efficiently.
Detailed technical explanation
How to think about this question
Composite models in Power BI allow mixing DirectQuery and Import tables in a single dataset, enabling real-time data from DirectQuery sources while historical data is cached for fast performance. Incremental refresh in Import mode uses Power Query's Range.Start and Range.End parameters to partition data by date, reducing refresh time and resource usage. The 15-minute latency requirement for current-month sales is achievable with DirectQuery to Azure SQL Database, which supports live queries without data movement.
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.
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FAQ
Questions learners often ask
What does this PL-300 question test?
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: Use a composite model: DirectQuery for the current month's sales data from Azure SQL, and Import mode for historical sales (with incremental refresh) and for customer feedback (with hourly refresh). Combine SharePoint files using Power Query and load them into the model using Import mode. Set up a DirectQuery connection for near real-time. — Option C is correct because it uses a composite model to meet all requirements: DirectQuery for near real-time current-month sales (≤15-minute latency), Import mode with incremental refresh for historical sales (daily refresh), Import mode for customer feedback (hourly refresh), and Power Query to combine SharePoint Excel files into a consistent table. This approach balances real-time needs with query performance and refresh flexibility, leveraging Power BI Premium's composite model capabilities.
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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Last reviewed: Jun 24, 2026
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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