Azure Data Scientists Associate Practice Exam

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What is a primary function of Azure Stream Analytics within a data science project?

To store large amounts of data for batch processing

To process and analyze real-time streaming data

Azure Stream Analytics is designed specifically for processing and analyzing real-time streaming data, making it a powerful tool in data science projects that require immediate insights from continuously flowing data streams. This capability allows data scientists to react to changing conditions in real-time, enabling applications such as monitoring sensor data, financial transactions, or social media feeds.

By focusing on the analysis of data as it arrives—rather than accumulating it for batch processing—Azure Stream Analytics can handle high-velocity data inputs and apply real-time transformations or computations. This allows organizations to gain insights instantly and often influences time-sensitive decision-making processes.

The other functions described, such as storing data for batch processing, visualizing data, or managing data warehouses, are not the core capabilities of Azure Stream Analytics, but rather relate to different Azure services that serve distinct purposes in data management and analysis workflows.

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To visualize data using dashboards and reports

To manage and secure data warehouses

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