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Answer: Source, target, and notebook libraries, ensuring the notebook libraries support real-time processing and are optimized for cost and scalability.
Option A is the correct answer because it comprehensively includes the source (data input), target (data output), and notebook libraries (for processing logic), with a focus on real-time processing, cost-effectiveness, scalability, and compliance with data governance policies. Option B misses the notebook libraries, which are crucial for data governance and processing logic. Option C lacks the notebook libraries component, essential for compliance and processing logic. Option D omits the source and target, which are fundamental components of any data pipeline.
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In the context of designing a Data Lake and Analytics (DLT) pipeline on Microsoft Azure, consider a scenario where your organization aims to process large volumes of data in real-time with minimal latency. The solution must be cost-effective, scalable, and comply with data governance policies. Which of the following components are essential to create the pipeline to meet these requirements? Choose the best option.
A
Source, target, and notebook libraries, ensuring the notebook libraries support real-time processing and are optimized for cost and scalability.
B
Source, transformation, and action, focusing on real-time data processing capabilities but without considering notebook libraries for data governance.
C
Source, target, and transformation, with transformations optimized for real-time processing but lacking explicit mention of compliance with data governance policies.
D
Transformation, action, and notebook libraries, emphasizing real-time processing and compliance but missing the source and target components.