Microsoft Certified Azure Data Fundamentals · Free Practice Question Medium
Question 4
Which of the following are true about stream processing? (Select all that apply)
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A
Stream processing typically has latency in the order of seconds or milliseconds.
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B
Stream processing typically handles large datasets in bulk.
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C
Stream processing always processes all historical data in a dataset.
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D
Stream processing is ideal for time-critical operations requiring real-time responses.
Reveal correct answers
Correct answers: A, D
Explanation
Stream processing is ideal for time-critical operations requiring real-time responses: This is incorrect because stream processing handles data in real-time as individual events, not in bulk.
Stream processing is ideal for time-critical operations requiring real-time responses: This is correct because stream processing is well-suited for time-critical operations that need immediate responses, such as triggering alarms or rebalancing stock portfolios.
Stream processing typically has latency in the order of seconds or milliseconds: This is correct because stream processing typically has low latency, often measured in seconds or milliseconds.
Stream processing always processes all historical data in a dataset: This is incorrect because stream processing usually focuses on recent data, rather than processing all historical data in a dataset.
Reference: https://learn.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/batch-processing
A. Stream processing typically has low latency in the order of seconds or milliseconds. This quick processing time enables real-time analytics, monitoring, and decision-making based on the most up-to-date data.
B. Stream processing does not typically handle large datasets in bulk. Instead, it processes data in real-time or near real-time, allowing for continuous data ingestion and processing without the need to store large amounts of data before processing.
C. Stream processing does not always process all historical data in a dataset. Depending on the use case and requirements, stream processing can focus on processing only the most recent data or a specific window of data, rather than processing all historical data.
D. Stream processing is ideal for time-critical operations that require real-time responses. It allows for the processing of data as it is generated, enabling immediate actions or decisions based on the incoming data.
Discussion
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