DP-900 Describe an analytics workload on Azure Practice Question
A data analyst needs to create a real-time dashboard in Power BI that refreshes every second from an Azure Stream Analytics job. Which Power BI feature should they use?
⚠ Common exam trap
Many exam-takers confuse scheduled refresh with real-time streaming, assuming that a high-frequency scheduled refresh can achieve sub-second updates, but Power BI's minimum scheduled refresh interval is 30 minutes, making it impossible for 1-second refreshes.
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
✓
Streaming dataset
B is correct because a streaming dataset in Power BI is designed to ingest real-time data from sources like Azure Stream Analytics and automatically update visuals as new data arrives. This feature supports push-based updates at sub-second intervals, making it ideal for a dashboard that refreshes every second without requiring manual or scheduled refresh cycles.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Scheduled refresh
Why it's wrong here
Scheduled refresh in Power BI imports data from a source at predefined intervals (e.g., every 15 minutes, hourly, or daily). Between refreshes, the dataset is static, so the dashboard reflects data only as of the last refresh. This makes it unsuitable for real-time dashboards that require continuous or sub-second updates. For true real-time, the data must flow into the model continuously rather than on a fixed schedule.
- ✓
Streaming dataset
Why this is correct
A streaming dataset in Power BI ingests data via an API or Azure Stream Analytics, updating visuals automatically as new data arrives. It supports near-real-time dashboards with latencies typically under one second. Unlike refresh-based approaches, streaming datasets keep the dashboard continuously updated without manual or scheduled polling. This is the appropriate choice for a real-time dashboard requirement.
- ✗
DirectQuery
Why it's wrong here
DirectQuery mode executes queries against the underlying source every time a visual is rendered, avoiding a full import refresh. However, each query incurs round-trip latency, and the source is typically not optimized for continuous sub-second queries. Power BI also imposes limits on query concurrency, and performance degrades with high-frequency updates. While it can be more timely than import, it is not designed for true real-time streaming.
- ✗
Import mode
Why it's wrong here
Import mode copies data into the Power BI in-memory model, providing fast query performance, but the data is a snapshot at the time of import. To update the dashboard, the dataset must be refreshed manually or on a schedule, creating lag. This mode is ideal for historical analysis but cannot deliver real-time updates. The lack of push-based ingestion makes it unsuitable for a real-time dashboard.
Go deeper
Related to this question
Learn chapter
Data Roles and Core Concepts
Key term
Azure Stream Analytics
Azure Stream Analytics is a fully managed, real-time data processing service that analyzes and transforms high volumes of streaming data from various sources to deliver low-latency insights and trigger actions.
Key term
Dataset
A dataset is a collection of related data, usually in a structured format, that can be used for analysis, training models, or reporting in Azure data services.
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