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Big Data and Distributed Computing MCQ Questions and Answers | Data Science MCQs

Explore our comprehensive collection of multiple-choice questions (MCQs) on Big Data and Distributed Computing designed to boost your confidence and knowledge in data science. These data science MCQs are essential for data science job interviews and exams. Page-7 section-1

61
In the context of big data, what does the term "data ingestion" refer to?
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Answer: Option B
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62
Which distributed computing framework is designed for low-latency, real-time data processing and is often used for building data pipelines and complex event processing (CEP)?
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Answer: Option A
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63
What is the primary challenge in processing and analyzing unstructured data in a big data environment?
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Answer: Option C
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64
In the context of big data storage, what does the term "data replication" involve?
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Answer: Option A
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65
Which distributed computing framework is commonly used for graph processing and can efficiently analyze large-scale graph data, such as social networks and recommendation systems?
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Answer: Option C
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66
What is the primary advantage of using a distributed file system like HDFS in big data environments?
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Answer: Option C
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67
In big data analytics, what is the primary goal of "data imputation"?
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Answer: Option C
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68
Which distributed computing framework is known for its in-memory data processing capabilities and is often used for iterative machine learning algorithms?
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Answer: Option C
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69
What does the term "data lineage" refer to in the context of big data analytics?
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Answer: Option C
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70
In a distributed computing environment, what is the primary role of a "Resource Manager" (ResourceManager) in the Hadoop ecosystem?
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Answer: Option B
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