DP-700 Question #126: Real Exam Question with Answer & Explanation

Question

You are designing a data solution in Microsoft Fabric that will process large volumes of streaming data from IoT devices. The data needs to be ingested, transformed, and made available for near real-time analytics. You need to choose the most appropriate Fabric component for ingesting and processing this streaming data. Which component should you use?

Options

• ADataflow Gen2
• BNotebooks
• CReal-Time hub with KQL Database
• DPipelines

Explanation

The question asks for the best Fabric component to ingest, transform, and analyze large volumes of IoT streaming data in near real-time.

Common mistakes.

• A. Dataflow Gen2 is primarily for batch ingestion and transformation, not optimized for the continuous, near real-time processing of large volumes of streaming data from IoT devices.
• B. Notebooks are versatile for data processing and analytics but are typically used for batch or interactive analysis, not as a primary, scalable engine for continuous ingestion and near real-time transformation of high-volume streaming data.
• D. Pipelines (data pipelines) are orchestration tools for moving and transforming data, often in batch. While they can include streaming-related activities, they are not the core component for the engine of streaming ingestion and near real-time analytics like the Real-Time hub and KQL Database.

Concept tested. Microsoft Fabric components for real-time streaming data ingestion and analytics

Reference. https://learn.microsoft.com/fabric/real-time/overview-real-time-analytics

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