Quick Answer
The answer is Power Query, the correct feature to combine data from multiple sources like Azure SQL Database and Azure Cosmos DB into a single Power BI report. Power Query serves as Power BI’s data connection and transformation engine, enabling you to merge, append, and shape disparate datasets through a graphical interface before loading them into the data model. On the DP-900 exam, this question tests your understanding of how Power Query handles data ingestion and integration across Azure services, often appearing as a scenario where you must choose between Power Query, DAX, or Power BI visuals—a common trap is confusing Power Query’s ETL role with DAX’s calculation functions. Remember that Power Query is the “prep” stage for combining and cleaning data, while DAX is for post-load analysis. A helpful memory tip: think of Power Query as the “mixer” that blends ingredients from different bowls (sources) into one batter (dataset) before baking your report.
This DP-900 practice question tests your understanding of describe core data concepts. 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.
A data analyst needs to combine sales data from Azure SQL Database and inventory data from Azure Cosmos DB into a single Power BI report. Which Power BI feature should they use?
Power Query
Power Query enables connecting to and merging data from multiple sources.
Power BI Desktop
Why wrong: Power BI Desktop is the application; the feature to combine data is Power Query.
DAX formulas
Why wrong: DAX is used for calculations on data already in the model, not for importing.
Dataflows
Why wrong: Dataflows are for reusable data preparation but are not the direct feature to combine sources in a report.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Power Query
Power Query is the correct feature because it is the data connection and transformation engine in Power BI that allows you to connect to multiple data sources—such as Azure SQL Database and Azure Cosmos DB—and combine them into a single dataset for reporting. It provides a graphical interface to merge, append, and shape data from disparate sources before loading it into the data model, which is exactly what the analyst needs to do.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Power Query
Why this is correct
Power Query enables connecting to and merging data from multiple sources.
Related concept
Read the scenario before looking for a memorised answer.
Power BI Desktop
Why it's wrong here
Power BI Desktop is the application; the feature to combine data is Power Query.
DAX formulas
Why it's wrong here
DAX is used for calculations on data already in the model, not for importing.
Dataflows
Why it's wrong here
Dataflows are for reusable data preparation but are not the direct feature to combine sources in a report.
Common exam traps
The trap here is that candidates often confuse the tool (Power BI Desktop) with the feature (Power Query), or they mistakenly think DAX is used for data integration, when in fact DAX operates only on data already in the model, not on source connections.
Detailed technical explanation
Under the hood, Power Query uses the M formula language to generate a query plan that can push down query logic to source systems (e.g., SQL queries to Azure SQL Database and SQL-like queries to Cosmos DB via the Azure Cosmos DB connector), reducing data movement. A subtle behavior is that Power Query can leverage native database queries (like 'SELECT * FROM Sales') or use its own folding logic, but if you use a custom SQL statement, query folding may break, causing all data to be pulled locally before merging—a performance trap in real-world scenarios.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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
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FAQ
Describe core data concepts — This question tests Describe core data concepts — Read the scenario before looking for a memorised answer..
The correct answer is: Power Query — Power Query is the correct feature because it is the data connection and transformation engine in Power BI that allows you to connect to multiple data sources—such as Azure SQL Database and Azure Cosmos DB—and combine them into a single dataset for reporting. It provides a graphical interface to merge, append, and shape data from disparate sources before loading it into the data model, which is exactly what the analyst needs to do.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
This DP-900 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 DP-900 exam.
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