This DP-900 practice question tests your understanding of describe an analytics workload on azure. 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.
Which THREE components are part of a typical modern data warehouse architecture on Azure? (Choose three.)
Azure Synapse Analytics
The data warehouse engine.
Power BI
Why wrong: Visualization tool, not part of data warehouse architecture.
Azure Stream Analytics
Why wrong: Real-time analytics, not core to modern data warehouse.
Azure Data Factory
Orchestrates ETL/ELT processes.
Azure Data Lake Storage Gen2
Used as the data lake layer.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Azure Synapse Analytics
Azure Synapse Analytics is a core component of a modern data warehouse architecture on Azure because it provides a unified analytics platform that combines big data and data warehousing capabilities. It enables T-SQL-based querying of both relational and non-relational data, integrating with Azure Data Lake Storage Gen2 for scalable storage and Azure Data Factory for orchestration.
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.
Azure Synapse Analytics
Why this is correct
The data warehouse engine.
Related concept
Read the scenario before looking for a memorised answer.
Power BI
Why it's wrong here
Visualization tool, not part of data warehouse architecture.
Azure Stream Analytics
Why it's wrong here
Real-time analytics, not core to modern data warehouse.
Azure Data Factory
Why this is correct
Orchestrates ETL/ELT processes.
Related concept
Read the scenario before looking for a memorised answer.
Azure Data Lake Storage Gen2
Why this is correct
Used as the data lake layer.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
The trap here is that candidates may confuse Power BI as a data warehouse component because it is commonly used with Azure Synapse, but it is a reporting/visualization layer, not part of the core storage, compute, or ingestion architecture.
Detailed technical explanation
In a modern data warehouse on Azure, Azure Synapse Analytics uses a distributed query engine (Massively Parallel Processing) that separates compute from storage, allowing independent scaling. Azure Data Lake Storage Gen2 provides a hierarchical namespace and POSIX-compliant access, enabling efficient data lake storage for raw and curated datasets. Azure Data Factory orchestrates data movement and transformation using control flow and data flow activities, often invoking PolyBase or COPY INTO for high-throughput loading into Synapse.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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
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FAQ
Describe an analytics workload on Azure — This question tests Describe an analytics workload on Azure — Read the scenario before looking for a memorised answer..
The correct answer is: Azure Synapse Analytics — Azure Synapse Analytics is a core component of a modern data warehouse architecture on Azure because it provides a unified analytics platform that combines big data and data warehousing capabilities. It enables T-SQL-based querying of both relational and non-relational data, integrating with Azure Data Lake Storage Gen2 for scalable storage and Azure Data Factory for orchestration.
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
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