DP-900 Describe an analytics workload on Azure Practice Question
Which THREE components are part of a typical modern data warehouse architecture on Azure? (Choose three.)
⚠ Common exam trap
A common mix-up: candidates 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.
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
✓
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.
Answer analysis
Option-by-option breakdown
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
Azure Synapse Analytics is the analytical serving engine of a modern data warehouse, providing dedicated SQL pools for massive parallel processing and serverless SQL endpoints for on-demand querying. It unifies data warehousing with big data analytics via Apache Spark, making it the place where curated data is structured into tabular models for high-performance relational queries. Without a purpose-built query engine like this, the lake alone cannot deliver fast, consistent relational performance.
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Power BI
Why it's wrong here
Power BI is a business intelligence and reporting tool that connects to a warehouse to build dashboards, paginated reports, and embedded visuals, so it operates downstream of the storage and compute layers. It does not ingest, transform, or govern data and contains no warehouse architecture of its own, making it a consumer surface rather than a data warehouse engine. For the DP-900 exam, Power BI is the front-end visualization layer, never a back-end platform component.
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Azure Stream Analytics
Why it's wrong here
Azure Stream Analytics is an event-processing engine designed for real-time data streams from IoT Edge, Event Hubs, or Kafka, performing time-windowed aggregations before data lands in a store. A classic enterprise warehouse relies on batch or micro-batch ETL/ELT to maintain historical state; streaming jobs may feed the lake but are not a structural pillar of the warehouse itself. The question asks about warehouse components, and this service remains on the real-time hot path, not the analytical store.
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Azure Data Factory
Why this is correct
Azure Data Factory is the orchestration and pipeline service that moves and transforms data in a modern warehouse, handling copy activities, mapping data flows, and executing stored procedures across heterogeneous sources. It is the control plane for loading raw data into Azure Data Lake Storage and scheduling incremental refresh of Synapse SQL tables, effectively serving as the ETL/ELT backbone. Without Data Factory, ingestion and transformation would be manual, but it is not a query engine and does not store data itself.
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Azure Data Lake Storage Gen2
Why this is correct
Azure Data Lake Storage Gen2 is a blob-storage-based data lake with a hierarchical namespace and POSIX permissions, providing a low-cost, scalable landing zone for raw and curated files. It stores Parquet, Avro, and JSON so Synapse Analytics and Azure Data Factory can query or transform them in-place, essentially acting as the persistence layer that separates storage from compute. This storage foundation enables schema-on-read, which is central to the lakehouse pattern and modern data warehouse architectures.
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Related to this question
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Data Roles and Core Concepts
Key term
Data warehouse
A data warehouse is a central repository that stores large amounts of structured data from multiple sources, optimized for querying and analysis rather than day-to-day transactions.
Key term
Azure Data Factory
Azure Data Factory is a cloud-based data integration service that lets you create, schedule, and orchestrate data pipelines to move and transform data from various sources to destinations.
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