DP-900 Describe an analytics workload on Azure Practice Question

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 and PolyBase

  Why it's wrong here

  Azure Synapse Analytics is a cloud-scale data warehouse and PolyBase is its feature for querying external data in files or other platforms using T-SQL. That combination is designed for large batch ETL/ELT and ad-hoc analytical queries over data at rest, not for continuous ingestion and low-latency stream processing. In a real-time dashboard, events would first have to be written to files or tables and then periodically loaded, adding unacceptable delay before visualization.

• ✗

  Azure Data Explorer and Azure Data Lake Storage

  Why it's wrong here

  Azure Data Explorer is a fast, interactive analytics engine for logs and telemetry, but when paired with Azure Data Lake Storage it is chiefly used to explore data files stored in the lake. The lake itself is an object-storage layer with file-based writes, so data lands there as files rather than as an active event stream; this file-oriented flow makes the pair batch-oriented rather than a true real-time ingestion pipeline. Moreover, neither service provides the native dashboard user interface needed to display live KPIs, so this combination would require a separate visualization tool.

• ✓

  Azure Stream Analytics and Power BI

  Why this is correct

  Azure Stream Analytics is a fully managed stream-processing engine that can consume millions of events per second from Event Hubs or IoT Hub, apply windowed aggregations, temporal filters, and pattern matching, and then emit results through its Power BI output sink. That output creates or updates a Power BI dataset in essentially real time, allowing the dashboard to refresh as new data arrives. Together they deliver the complete path from live streaming source to interactive visual dashboard, which is exactly what the company needs.

• ✗

  Azure Analysis Services and Excel

  Why it's wrong here

  Azure Analysis Services is a tabular modeling layer that creates compressed, in-memory semantic models for business intelligence; Excel can connect to these models via a PivotTable, but both rely on data already loaded and structured. Refreshes are scheduled or batch-driven, and the service offers no native streaming ingestion, so a dashboard built this way would only reflect the last refresh, not live events. Excel is also a desktop reporting tool, not a continuously updating cloud dashboard for real-time monitoring.

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