DBATU Remedial Exam IMP MCQ PDF | IMP MCQ PDF

 DBATU Remedial Exam IMP MCQ  PDF For BIG Data Analysis

  1. What is big data? a) Large amounts of structured data b) Large amounts of unstructured data c) Both structured and unstructured data d) Data that can be easily processed

Answer: b) Large amounts of unstructured data

  1. Which of the following is NOT a characteristic of big data? a) Volume b) Variety c) Velocity d) Validity

Answer: d) Validity

  1. Which technology is commonly used for storing and processing big data? a) Relational databases b) Cloud computing c) Mainframe computers d) USB drives

Answer: b) Cloud computing

  1. What is the primary goal of big data analytics? a) Storing data efficiently b) Extracting insights and value from data c) Securing data from unauthorized access d) Reducing the size of data sets

Answer: b) Extracting insights and value from data

  1. Which programming language is often used for big data analytics? a) Java b) Python c) C++ d) Ruby

  1. What is the process of transforming raw data into a more useful format for analysis called? a) Data integration b) Data visualization c) Data preprocessing d) Data encryption

Answer: b) Python

Show Answer: c) Data preprocessing

  1. Which of the following is an example of a big data processing framework? a) Hadoop b) MySQL c) Oracle d) MongoDB

Show Answer: a) Hadoop

  1. What is the term for a collection of data that is too large and complex to be processed by traditional database management tools? a) Small data b) Medium data c) Big data d) Mega data

Show Answer: c) Big data

  1. Which of the following is NOT a common challenge in big data analysis? a) Data privacy and security b) Data storage limitations c) Data quality and accuracy d) Data visualization techniques

Show Answer: d) Data visualization techniques

  1. What is the purpose of data mining in big data analytics? a) Identifying patterns and relationships in data b) Storing and organizing large datasets c) Cleaning and preprocessing data d) Encrypting sensitive data

Show Answer: a) Identifying patterns and relationships in data

  1. Which of the following is an example of an unstructured data source? a) Sensor data b) Relational database c) Excel spreadsheet d) Social media posts

Show Answer: d) Social media posts

  1. What does ETL stand for in the context of big data analytics? a) Extract, Transform, Load b) Explore, Test, Learn c) Execute, Track, Log d) Encode, Transfer, Link

Show Answer: a) Extract, Transform, Load

  1. Which statistical technique is commonly used for predictive analytics in big data analysis? a) Linear regression b) Cluster analysis c) Principal component analysis d) Hypothesis testing

Show Answer: a) Linear regression

  1. What is the term for the process of discovering hidden patterns and knowledge from large volumes of data? a) Data exploration b) Data validation c) Data transformation

d) Data discovery

  1. Which of the following is a data visualization technique used in big data analysis? a) Bar charts b) Scatter plots c) Heat maps d) All of the above

Answer: d) All of the above

  1. What is the term for the ability of a system to process and analyze data in real-time? a) Real-time processing b) Stream processing c) Batch processing d) Offline processing

Answer: b) Stream processing

  1. Which of the following is NOT a popular big data analytics tool? a) Apache Spark b) Tableau c) SAS d) TensorFlow

Answer: b) Tableau

  1. Which technique is used to reduce the dimensionality of big data while preserving important information? a) Clustering b) Sampling c) Feature selection d) Anomaly detection

Answer: c) Feature selection

  1. What is the term for the process of cleaning and correcting data before analysis? a) Data wrangling b) Data mining c) Data modeling d) Data partitioning

Answer: a) Data wrangling

  1. Which of the following is an example of a big data application? a) Fraud detection b) Weather forecasting c) Personalized recommendations d) All of the above

  1. What is the term for a set of techniques used to uncover insights from textual data? a) Text mining b) Image recognition c) Speech processing d) Natural language processing

Answer: a) Text mining

  1. Which of the following is a commonly used big data file format? a) CSV b) XML c) JSON d) All of the above

Answer: d) All of the above

  1. Which of the following is a privacy concern associated with big data analysis? a) Unauthorized access to sensitive data b) Inaccurate analysis results c) Data duplication d) Slow processing speed

Answer: a) Unauthorized access to sensitive data

  1. What is the term for the ability of a system to handle increasing data volumes without sacrificing performance? a) Scalability b) Flexibility c) Interoperability d) Robustness

Answer: a) Scalability

  1. Which technique is used to identify outliers and anomalies in big data sets? a) Clustering b) Regression analysis c) Classification d) Anomaly detection

Answer: d) Anomaly detection

  1. What is the role of a data scientist in big data analysis? a) Data collection and storage b) Data visualization and reporting c) Data interpretation and modeling d) Data security and encryption

Answer: c) Data interpretation and modeling

  1. Which of the following is NOT a big data visualization tool? a) Power BI b) QlikView c) D3.js d) Apache Kafka

Answer: d) Apache Kafka

  1. What is the term for the process of combining data from different sources into a single coherent dataset? a) Data integration b) Data segmentation c) Data aggregation d) Data encryption

Answer: a) Data integration

  1. Which technique is used to classify data into different groups or categories in big data analysis? a) Regression analysis b) Clustering c) Association

Answer: b) Clustering

analysis d) Decision trees

  1. What is the term for the ability to analyze and process data at the location where it is generated? a) Edge computing b) Cloud computing c) Centralized computing d) Distributed computing

Answer: a) Edge computing


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