Big Data and Distributed Computing MCQ Questions and Answers

61.
In the context of big data, what does the term "data ingestion" refer to?

A. The process of extracting insights from data

B. The process of collecting and importing data

C. The process of visualizing data

D. The process of reducing data volume

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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)?

A. Apache Kafka

B. Apache HBase

C. Apache Spark Streaming

D. Apache Hive

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63.
What is the primary challenge in processing and analyzing unstructured data in a big data environment?

A. Limited data volume

B. Data skew

C. Data variety

D. Data veracity

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64.
In the context of big data storage, what does the term "data replication" involve?

A. The duplication of data across multiple nodes

B. The reduction of data variety

C. The distribution of data across clusters

D. The encryption of data

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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?

A. Apache Kafka

B. Apache HBase

C. Apache Spark GraphX

D. Apache Hive

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66.
What is the primary advantage of using a distributed file system like HDFS in big data environments?

A. Data scalability

B. Simplicity of programming

C. Scalability and fault tolerance

D. Real-time data collection and analysis

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67.
In big data analytics, what is the primary goal of "data imputation"?

A. To reduce data variety

B. To increase data volume

C. To fill missing values in the data

D. To decrease data velocity

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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?

A. Apache Kafka

B. Apache HBase

C. Apache Spark

D. Apache Hive

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69.
What does the term "data lineage" refer to in the context of big data analytics?

A. The process of collecting data

B. The process of storing data

C. The tracking of data's origins and changes

D. The process of visualizing data

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70.
In a distributed computing environment, what is the primary role of a "Resource Manager" (ResourceManager) in the Hadoop ecosystem?

A. Storing metadata

B. Managing job scheduling

C. Storing and managing data blocks

D. Managing data visualization

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

61. In the context of big data, what does the term "data ingestion" refer to?

Answer & Solution

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)?

Answer & Solution

63. What is the primary challenge in processing and analyzing unstructured data in a big data environment?

Answer & Solution

64. In the context of big data storage, what does the term "data replication" involve?

Answer & Solution

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?

Answer & Solution

66. What is the primary advantage of using a distributed file system like HDFS in big data environments?

Answer & Solution

67. In big data analytics, what is the primary goal of "data imputation"?

Answer & Solution

68. Which distributed computing framework is known for its in-memory data processing capabilities and is often used for iterative machine learning algorithms?

Answer & Solution

69. What does the term "data lineage" refer to in the context of big data analytics?

Answer & Solution

70. In a distributed computing environment, what is the primary role of a "Resource Manager" (ResourceManager) in the Hadoop ecosystem?

Answer & Solution

61.
In the context of big data, what does the term "data ingestion" refer to?

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)?

63.
What is the primary challenge in processing and analyzing unstructured data in a big data environment?

64.
In the context of big data storage, what does the term "data replication" involve?

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?

66.
What is the primary advantage of using a distributed file system like HDFS in big data environments?

67.
In big data analytics, what is the primary goal of "data imputation"?

68.
Which distributed computing framework is known for its in-memory data processing capabilities and is often used for iterative machine learning algorithms?

69.
What does the term "data lineage" refer to in the context of big data analytics?

70.
In a distributed computing environment, what is the primary role of a "Resource Manager" (ResourceManager) in the Hadoop ecosystem?