DP-900 Describe an analytics workload on Azure Practice Question
A healthcare organization must build an analytics solution that processes streaming patient vitals data and provides real-time dashboards. The solution must also store historical data for compliance audits. Which combination of Azure services should the organization use?
⚠ Common exam trap
Candidates often confuse Azure Synapse Analytics as a streaming service due to its 'analytics' name, but it is primarily a data warehouse for batch and interactive queries, not for real-time stream processing.
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 Stream Analytics for real-time processing and Azure SQL Database for historical storage and dashboards.
Azure Stream Analytics is purpose-built for real-time processing of streaming data, such as patient vitals, and can output directly to Power BI for live dashboards. Azure SQL Database provides a relational store for historical data, supporting compliance audits with point-in-time restore and long-term retention. This combination meets both real-time and historical requirements without unnecessary complexity.
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 Stream Analytics for real-time processing and Azure SQL Database for historical storage and dashboards.
Why this is correct
Azure Stream Analytics is purpose-built for low-latency, real-time processing with a SQL-like query language over streaming inputs, enabling windowed aggregations and filtering for patient monitoring. Azure SQL Database provides a managed relational store with ACID transactions, indexes, and T-SQL support, making it appropriate for structured historical data and compliance-driven audit queries. Power BI can query SQL Database directly for paginated and interactive dashboards, while Stream Analytics can land processed rows into SQL Database for a unified serving path.
- ✗
Azure Synapse Analytics for real-time processing and Azure Blob Storage for archival.
Why it's wrong here
Azure Synapse Analytics is an enterprise data warehouse and analytics service designed for large-scale batch and interactive querying of data, not for ingesting and processing real-time telemetry streams with millisecond-level latency; that is the job of Stream Analytics or Event Hubs. Azure Blob Storage offers cheap, tiered object storage that is good for archival data, but it is not a relational store and does not natively support T-SQL queries or dashboard-style access, so a healthcare organization would still need an additional query engine for historical reporting. Simply pairing Synapse for streaming and Blob for archival leaves the actual stream-processing step unhandled, creating a gap in the real-time path.
- ✗
Azure Event Hubs for ingestion and Azure Data Lake Storage for storage, with Power BI for dashboards.
Why it's wrong here
Azure Event Hubs is a highly scalable event ingestion service that can accept millions of events per second, but it does not perform transformations, enrichment, windowing, or alerting—it only buffers and delivers events to consumers. Azure Data Lake Storage Gen2 provides durable, hierarchical file storage for raw or curated data files, yet Power BI cannot directly query those files in real time; a serving layer such as SQL Database or a query engine is required to expose the data. The combination omits a stream-processing component (e.g., Stream Analytics) and a structured serving store, so it is incomplete for a real-time analytics solution.
- ✗
Azure HDInsight with Apache Spark for streaming and Azure Cosmos DB for storage.
Why it's wrong here
HDInsight with Apache Spark can run micro-batch or structured streaming, but it introduces significant cluster management overhead and is better suited for large-scale batch ETL; it is not a turnkey, fully managed real-time processing service like Stream Analytics. Azure Cosmos DB is a multi-model NoSQL database optimized for operational and transactional workloads with single-digit-millisecond reads/writes, not for immutable, append-only audit storage or complex relational reporting for compliance. Using Cosmos DB for healthcare audit logs would require custom partitioning and serialization, and it lacks the straightforward SQL compatibility and cost profile of Azure SQL Database for typical compliance dashboards.
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Data Roles and Core Concepts
Key term
Data
Data is raw, unprocessed information, like numbers, words, or measurements, that can be stored, processed, and analyzed by computers.
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Power BI
Power BI is a Microsoft business analytics tool that transforms raw data into interactive visual reports and dashboards for informed decision-making.
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