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Big Data And Distributed Computing MCQs

Practice Big Data And Distributed Computing MCQs for competitive exams.

Big Data And Distributed Computing MCQs

Practice questions from this topic.

In big data analytics, what is the term for the process of summarizing data to discover patterns, trends, and insights that can inform decision-making?

  1. A. Data sampling
  2. B. Data integration
  3. C. Data transformation
  4. D. Data visualization
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In the context of big data, what is the term for the process of preparing and transforming data so that it can be effectively analyzed and visualized?

  1. A. Data sampling
  2. B. Data preprocessing
  3. C. Data deduplication
  4. D. Data siloing
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What is the primary advantage of using data lakes in big data architectures?

  1. A. Centralized storage for structured data
  2. B. Scalability and fault tolerance
  3. C. Handling unstructured data
  4. D. Reduced data storage and transmission costs
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In a distributed computing environment, what is the primary role of a "Resource Manager" (ResourceManager) in the Hadoop ecosystem?

  1. A. Storing metadata
  2. B. Managing job scheduling
  3. C. Storing and managing data blocks
  4. D. Managing data visualization
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What does the term "data lineage" refer to in the context of big data analytics?

  1. A. The process of collecting data
  2. B. The process of storing data
  3. C. The tracking of data's origins and changes
  4. D. The process of visualizing data
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Which distributed computing framework is known for its in-memory data processing capabilities and is often used for iterative machine learning algorithms?

  1. A. Apache Kafka
  2. B. Apache HBase
  3. C. Apache Spark
  4. D. Apache Hive
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In big data analytics, what is the primary goal of "data imputation"?

  1. A. To reduce data variety
  2. B. To increase data volume
  3. C. To fill missing values in the data
  4. D. To decrease data velocity
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What is the primary advantage of using a distributed file system like HDFS in big data environments?

  1. A. Data scalability
  2. B. Simplicity of programming
  3. C. Scalability and fault tolerance
  4. D. Real-time data collection and analysis
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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?

  1. A. Apache Kafka
  2. B. Apache HBase
  3. C. Apache Spark GraphX
  4. D. Apache Hive
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In the context of big data storage, what does the term "data replication" involve?

  1. A. The duplication of data across multiple nodes
  2. B. The reduction of data variety
  3. C. The distribution of data across clusters
  4. D. The encryption of data
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What is the primary challenge in processing and analyzing unstructured data in a big data environment?

  1. A. Limited data volume
  2. B. Data skew
  3. C. Data variety
  4. D. Data veracity
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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)?

  1. A. Apache Kafka
  2. B. Apache HBase
  3. C. Apache Spark Streaming
  4. D. Apache Hive
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