What Do You Know About Big Data Tools?

Reviewed by Samy Boulos
Samy Boulos, MSc (Computer Science) |
Data Engineer
Review Board Member
Samy Boulos is an experienced Technology Consultant with a diverse 25-year career encompassing software development, data migration, integration, technical support, and cloud computing. He leverages his technical expertise and strategic mindset to solve complex IT challenges, delivering efficient and innovative solutions to clients.
, MSc (Computer Science)
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What Do You Know About Big Data Tools? - Quiz

Welcome to our Big Data Tools Quiz! This quiz is crafted for data professionals, analysts, and enthusiasts eager to test their knowledge and skills in the rapidly evolving field of big data. Big data tools are essential for handling massive volumes of data efficiently, providing insights that drive strategic decisions across industries.

Each question aims to assess your understanding of these tools’ functionalities, best practices for their use, and scenarios for their application. Whether you are a seasoned expert looking to validate your expertise or a newcomer aiming to break into the field, this quiz provides a comprehensive evaluation of Read moreyour mastery of big data tools. Dive in and see how well-equipped you are to leverage the power of big data in your projects and career!


Big Data Tools Questions and Answers

  • 1. 

    Which of the following is the most prominent and used tool in the Big Data industry with its enormous capability of large-scale processing data?

    • A.

      Cassandra

    • B.

      Apache Storm 

    • C.

      Apache Stark 

    • D.

      Hadoop 

    Correct Answer
    D. Hadoop 
    Explanation
    Hadoop is the most prominent and used tool in the big data industry due to its enormous capability of large-scale processing data. It is an open-source framework that allows for distributed storage and processing of large datasets across computer clusters. Hadoop's distributed file system (HDFS) enables data to be stored and processed across multiple machines, while its MapReduce programming model allows for parallel processing of data. With its scalability, fault tolerance, and ability to handle vast amounts of data, Hadoop has become the go-to tool for big data processing.

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  • 2. 

    Which of the following is flexible to work with HDFS as well as with other data stores? 

    • A.

      Cassandra

    • B.

      Apache Storm

    • C.

      Apache Spark

    • D.

      Hadoop

    Correct Answer
    C. Apache Spark
    Explanation
    Apache Spark is flexible to work with HDFS as well as with other data stores. Spark provides a unified analytics engine that supports various data processing tasks, including batch processing, streaming, machine learning, and graph processing. It can seamlessly integrate with Hadoop and HDFS, allowing users to leverage their existing Hadoop clusters and data stored in HDFS. Additionally, Spark also supports other data sources such as Cassandra, MongoDB, Amazon S3, and more, making it a versatile choice for data processing and analytics across different data stores.

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  • 3. 

    Which of the following has this unique feature, ‘massive scalability’? 

    • A.

      Cassandra 

    • B.

      Apache Storm 

    • C.

      Apache Spark

    • D.

      Hadoop 

    Correct Answer
    B. Apache Storm 
    Explanation
    Apache Storm has the unique feature of "massive scalability". Apache Storm is a distributed real-time computation system that allows for processing large amounts of data in a scalable and fault-tolerant manner. It is designed to handle high velocity streaming data and can scale to handle large workloads by distributing the processing across multiple nodes in a cluster. This makes it an ideal choice for applications that require real-time data processing and have high scalability requirements.

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  • 4. 

    Which of the following mainly processes data sets? 

    • A.

      Cassandra 

    • B.

      Apache Storm

    • C.

      Apache Spark

    • D.

      Hadoop 

    Correct Answer
    A. Cassandra 
    Explanation
    Cassandra is a distributed database management system that is designed to handle large amounts of data across multiple servers. It is mainly used for processing and storing data sets, making it the correct answer for this question. Apache Storm, Apache Spark, and Hadoop are also used for processing big data, but they have different functionalities and purposes compared to Cassandra.

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  • 5. 

    Which of the following follows a client/server model where the server could be located on-premise? 

    • A.

      RapidMiner

    • B.

      MongoDB 

    • C.

      R Programming Tool 

    • D.

      Neo4j

    Correct Answer
    A. RapidMiner
    Explanation
    RapidMiner follows a client/server model where the server can be located on-premise. This means that the software can be installed on a local server within an organization's infrastructure, allowing for greater control and security over the data being processed and analyzed. The client, or user interface, can then connect to the server to access and utilize the data mining and analytics capabilities of RapidMiner. This client/server model is beneficial for organizations that prefer to keep their data and analysis processes within their own network rather than relying on cloud-based solutions.

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  • 6. 

    Which of the following is ideal for the business that needs fast and real-time data for instant decisions? 

    • A.

      RapidMiner

    • B.

      MongoDB 

    • C.

      R Programming Tool 

    • D.

      Neo4j

    Correct Answer
    B. MongoDB 
    Explanation
    MongoDB is ideal for a business that needs fast and real-time data for instant decisions because it is a NoSQL database that offers high performance and scalability. It allows for the storage and retrieval of large volumes of data in real-time, making it suitable for applications that require quick access to data for decision-making. MongoDB's flexible document model and distributed architecture enable it to handle high-speed data processing, making it a suitable choice for businesses that need fast and real-time data analysis.

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  • 7. 

    Which data tool allows for one not to necessarily be a statistical expert before it can be made use of although used for statistical analysis? 

    • A.

      RapidMiner

    • B.

      MongoDB 

    • C.

      R Programming Tool 

    • D.

      Neo4j

    Correct Answer
    C. R Programming Tool 
    Explanation
    R Programming Tool allows for one not to necessarily be a statistical expert before it can be made use of although used for statistical analysis. R is a programming language and software environment specifically designed for statistical computing and graphics. It provides a wide range of statistical and graphical techniques, making it accessible for users with varying levels of statistical expertise.

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  • 8. 

    Which data tool does one need to deal with large volumes of network data or graph-related issues like social networking or demographic patterns? 

    • A.

      RapidMiner

    • B.

      MongoDB 

    • C.

      R Programming Tool 

    • D.

      Neo4j

    Correct Answer
    D. Neo4j
    Explanation
    Neo4j is the correct answer because it is a data tool specifically designed to handle large volumes of network data or graph-related issues. It is a graph database that allows for efficient storage, retrieval, and analysis of interconnected data, making it ideal for tasks such as analyzing social networks or demographic patterns. RapidMiner, MongoDB, and R Programming Tool are not specifically designed for handling network data or graph-related issues, making them incorrect choices.

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  • 9. 

    Which data tool is regarded as being very necessary before stepping into the Big Data industry? 

    • A.

      HPCC

    • B.

      Neo4j

    • C.

      Hadoop

    • D.

      Cassandra

    Correct Answer
    C. Hadoop
    Explanation
    Hadoop is regarded as being very necessary before stepping into the big data industry. Hadoop is an open-source framework that allows for the distributed processing of large datasets across clusters of computers. It provides a scalable and reliable platform for storing, managing, and analyzing big data. Hadoop's ability to handle large volumes of data, its fault-tolerance, and its ability to process data in parallel make it an essential tool for working with big data.

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  • 10. 

    What does HPCC stand for?

    • A.

      High-Performance Computing Cluster

    • B.

      High-performance Computer Carrier  

    • C.

       Hit Primary Computing Cloud   

    • D.

      High Primary Computing Card

    Correct Answer
    A. High-Performance Computing Cluster
    Explanation
    HPCC stands for High-Performance Computing Cluster. This term refers to a group of computers connected together to work as a single system, providing high-performance computing capabilities. This cluster is designed to handle complex and computationally intensive tasks, such as scientific simulations, data analysis, and large-scale data processing. By harnessing the power of multiple computers working in parallel, HPCCs can significantly speed up calculations and improve overall performance.

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Samy Boulos |MSc (Computer Science) |
Data Engineer
Samy Boulos is an experienced Technology Consultant with a diverse 25-year career encompassing software development, data migration, integration, technical support, and cloud computing. He leverages his technical expertise and strategic mindset to solve complex IT challenges, delivering efficient and innovative solutions to clients.

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  • Current Version
  • May 08, 2024
    Quiz Edited by
    ProProfs Editorial Team

    Expert Reviewed by
    Samy Boulos
  • Aug 25, 2019
    Quiz Created by
    Gregorynaomi
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