DP-900 Describe an analytics workload on Azure Practice Question
A data analyst needs to create a report in Power BI that combines sales data from Azure SQL Database and inventory data from Azure Cosmos DB. The report should refresh daily. Which Power BI feature should be used to combine these data sources?
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
✓
Power Query
Power Query allows connecting to multiple data sources (like Azure SQL Database and Azure Cosmos DB) and combining them through merge or append queries. This is the correct feature for combining data from different sources. Option A (Quick Measures) is for creating quick calculations within a single table, not for combining sources. Option B (DAX) is a formula language used for creating calculated columns or measures, not for data ingestion or combining sources. Option C (Power BI Desktop) is the application itself, not a specific feature for combining data.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Quick Measures
Why it's wrong here
Quick Measures are pre-built DAX formula templates in Power BI for common calculations such as year-over-year change or rolling average. They operate on data that is already loaded into the data model, so they cannot connect to, ingest, or combine external data sources. Using Quick Measures would require the disparate data to already exist in a single table, which is precisely the problem the analyst needs to solve first.
- ✗
Data Analysis Expressions (DAX)
Why it's wrong here
Data Analysis Expressions (DAX) is a functional language used to create calculated columns, measures, and row-level security in the Power BI data model. It evaluates expressions against data that is already present in memory, and it does not provide any connectors or query logic to pull data from multiple sources. Combining data at the source level is outside DAX's scope; it only manipulates the combined dataset after Power Query has done its job.
- ✗
Power BI Desktop
Why it's wrong here
Power BI Desktop is the standalone application used to build reports, but it is not a single feature designed for data integration. Data connectivity and shaping happen inside Power Query, which is embedded in Power BI Desktop as the query editor. Therefore, choosing Power BI Desktop overstates the answer; the correct feature-level tool is specifically Power Query, not the broader hosting environment.
- ✓
Power Query
Why this is correct
Power Query is Microsoft's data connection and transformation engine that supports hundreds of data sources, including databases, files, and web services. Its query editor allows merging tables (like SQL JOINs) and appending rows (like UNIONs) to combine sources into a single dataset before loading into the data model. This makes it the precise tool for the analyst's requirement to bring multiple data sources together for a report.
Go deeper
Related to this question
Learn chapter
Data Roles and Core Concepts
Key term
Azure Cosmos DB
Azure Cosmos DB is a fully managed, globally distributed NoSQL database service that offers fast reads and writes anywhere in the world with automatic scaling and multiple consistency models.
Key term
Data ingestion
Data ingestion is the process of moving data from various sources into a storage system where it can be accessed, analyzed, and used.
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