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Big Data Multiple Choice Questions [2024]


Big Data Multiple Choice Questions [2024]

Big Data Interview Questions and Answers Preparation Practice Test | Freshers to Experienced | Detailed Explanations.

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1. What is the primary characteristic that distinguishes Big Data from traditional data processing?

a. Volume

b. Variety

c. Velocity

d. Veracity

Explanation: Big Data is characterized by the 3Vs: Volume, Variety, and Velocity. While Veracity is also a significant concern, the primary distinguishing factor is the sheer Volume of data.

2. Which programming model is commonly used for processing large datasets in a distributed computing environment?

a. Object-Oriented Programming

b. Procedural Programming

c. MapReduce

d. Functional Programming

Explanation: MapReduce is a programming model commonly used for processing large datasets in a distributed computing environment. It allows for parallel processing and scalability.

3. What is the purpose of Hadoop in the context of Big Data?

a. Data Storage

b. Data Processing

c. Data Visualization

d. Data Security

Explanation: Hadoop is primarily used for distributed storage and processing of large datasets. It provides a scalable and fault-tolerant framework for handling Big Data.

4. Which of the following technologies is used for real-time data processing in Big Data systems?

a. Hadoop

b. Spark

c. Hive

d. Kafka

Explanation: Kafka is a distributed streaming platform that is commonly used for real-time data processing in Big Data systems. It enables the handling of high-throughput, fault-tolerant data streams.

5. What is the primary role of Apache Spark in Big Data processing?

a. Data Storage

b. Data Analysis

c. Data Ingestion

d. Data Orchestration

Explanation: Apache Spark is used for data analysis in Big Data processing. It provides a fast and general-purpose cluster computing system for big data.

6. Which data storage technology is commonly associated with the Hadoop ecosystem for handling large-scale distributed storage?

a. NoSQL databases

b. Relational databases

c. Columnar databases

d. Hadoop Distributed File System (HDFS)

Explanation: Hadoop Distributed File System (HDFS) is the storage system commonly associated with the Hadoop ecosystem. It is designed for handling large-scale distributed storage.

7. In the context of Big Data, what does the term "Data Lake" refer to?

a. Centralized data repository

b. Real-time data processing

c. Streamlined data analytics

d. Data encryption technique

Explanation: A Data Lake is a centralized repository that allows storing vast amounts of raw data in its native format until it's needed. It provides a flexible and scalable solution for data storage.

8. Which of the following is an example of unstructured data in the context of Big Data?

a. Relational databases

b. CSV files

c. Images

d. JSON documents

Explanation: Images are an example of unstructured data. Unstructured data does not have a predefined data model and can include various types of content, such as images, videos, and text.

9. What is the role of data preprocessing in Big Data analytics?

a. Storing data in databases

b. Cleaning and transforming raw data

c. Analyzing processed data

d. Securing data storage

Explanation: Data preprocessing involves cleaning and transforming raw data into a format suitable for analysis. It is a crucial step in Big Data analytics to ensure the accuracy and reliability of results.

10. Which of the following is a common challenge in ensuring the quality of Big Data?

a. Low data volume

b. Data homogeneity

c. Data privacy concerns

d. Simple data structures

Explanation: Data privacy concerns are a common challenge in ensuring the quality of Big Data. Handling sensitive information and complying with privacy regulations are critical considerations in Big Data processing.

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