Big Data And Distributed Computing — Part 2 MCQs with Explanations

Limited data reliability is the correct answer to “In big data analytics, what is the primary challenge associated with "data veracity"”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

Real-time data processing is the correct answer to “What is the primary benefit of using a distributed data processing framework like Apache Spark over traditional batch processing systems”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

Flexible schema and scalability is the correct answer to “What is the main advantage of using a "NoSQL" database in big data applications”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

To improve data quality is the correct answer to “What is the primary purpose of "data cleansing" in big data preprocessing”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

To enhance data with additional information is the correct answer to “In the context of big data analytics, what is the primary goal of "data enrichment"”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

Storing metadata is the correct answer to “In a distributed computing cluster, what is the primary role of a "Master Node" (or NameNode) in the Hadoop ecosystem”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

Apache Spark Streaming is the correct answer to “Which distributed computing framework is designed for real-time data stream processing and is often used for analyzing event data and monitoring applications”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

Data skew is the correct answer to “What is the primary challenge in processing and analyzing data with high velocity in a big data environment”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

To distribute data across multiple nodes is the correct answer to “In a distributed computing environment, what is the purpose of "data partitioning" or "sharding"”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

Processing data in fixed-size batches is the correct answer to “What does the term "batch processing" typically refer to in the context of big data analytics”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

Apache Spark is the correct answer to “Which distributed computing framework is known for its high-speed, low-latency data processing capabilities and is suitable for real-time analytics”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

To reduce storage space and data redundancy is the correct answer to “What is the primary goal of "data deduplication" in big data storage and processing”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

Managing job scheduling is the correct answer to “In distributed computing, what is the primary purpose of a "Job Tracker" in the Hadoop MapReduce framework”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

Apache Drill is the correct answer to “Which distributed computing framework is commonly used for interactive data analytics and SQL-like querying of large datasets in real-time”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

Preparing data for analysis is the correct answer to “In big data analytics, what does the term "data transformation" involve”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

Scalability and parallel processing capabilities is the correct answer to “What is the primary advantage of using distributed data processing frameworks like Hadoop and Spark for big data analytics”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

Data integration is the correct answer to “In the context of big data analytics, what is the term for the process of combining data from multiple sources and formats into a single, unified dataset”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

To process and aggregate data from Mapper tasks is the correct answer to “What is the main purpose of a "Combiner" in the Hadoop MapReduce programming model”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

To process and aggregate data from Mapper tasks is the correct answer to “In distributed computing, what is the primary advantage of using a "Reducer" in the MapReduce programming model”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

Analyzing and extracting insights from data is the correct answer to “What is the primary role of a "Data Scientist" in the context of big data analytics”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

The process of collecting and importing data is the correct answer to “In the context of big data, what does the term "data ingestion" refer to”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

Apache Kafka is the correct answer to “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)”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

Data variety is the correct answer to “What is the primary challenge in processing and analyzing unstructured data in a big data environment”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

The duplication of data across multiple nodes is the correct answer to “In the context of big data storage, what does the term "data replication" involve”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

Apache Spark GraphX is the correct answer to “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”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

Scalability and fault tolerance is the correct answer to “What is the primary advantage of using a distributed file system like HDFS in big data environments”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

To fill missing values in the data is the correct answer to “In big data analytics, what is the primary goal of "data imputation"”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

Apache Spark is the correct answer to “Which distributed computing framework is known for its in-memory data processing capabilities and is often used for iterative machine learning algorithms”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

The tracking of data's origins and changes is the correct answer to “What does the term "data lineage" refer to in the context of big data analytics”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

Managing job scheduling is the correct answer to “In a distributed computing environment, what is the primary role of a "Resource Manager" (ResourceManager) in the Hadoop ecosystem”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

Handling unstructured data is the correct answer to “What is the primary advantage of using data lakes in big data architectures”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

Data preprocessing is the correct answer to “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”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.

Data visualization is the correct answer to “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”. This question is standard in competitive examination syllabi for Big Data And Distributed Computing.