Databricks Certified Data Analyst Associate · Free Practice Question Medium
Question 11
Which of the following best describes the capability of a Lakehouse architecture, particularly within Databricks, regarding data processing workloads?
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A
It exclusively supports real-time streaming workloads, designed for continuous data ingestion and analysis.
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B
It restricts data processing to batch workloads only, optimizing for large-scale batch processing.
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C
It separates batch and streaming workloads, requiring dedicated environments for each type of processing.
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D
It requires manual synchronization between batch and streaming processes, with limited automation.
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E
It allows for the seamless integration of batch and streaming workloads within a unified platform.
Reveal correct answer
Correct answer: E
Explanation
B. It allows for the seamless integration of batch and streaming workloads within a unified platform.
The Lakehouse architecture, as implemented in platforms like Databricks, is designed to support the seamless integration of both batch and streaming workloads within a single, unified environment. This capability is one of the key strengths of the Lakehouse approach, allowing organizations to handle diverse data processing needs—whether they involve processing large volumes of historical data in batch mode or ingesting and analyzing real-time data streams. By enabling both types of workloads to coexist and interact within the same platform, the Lakehouse provides a versatile and efficient solution for modern data management and analytics, eliminating the need for separate systems and reducing complexity.
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Discussion
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