Q.1 What is the primary goal of integrating Big Data with Cloud Computing?
Data visualization
Cost reduction and scalability
Creating backup copies
Software testing
Explanation - Integrating Big Data with Cloud allows organizations to process large volumes of data efficiently while reducing infrastructure costs and ensuring scalability.
Correct answer is: Cost reduction and scalability
Q.2 Which cloud service model is most commonly used for Big Data analytics?
IaaS
PaaS
SaaS
FaaS
Explanation - PaaS provides pre-configured environments for analytics, making it the most suitable for Big Data workloads compared to IaaS or SaaS.
Correct answer is: PaaS
Q.3 Which of the following is an example of Big Data framework often used in Cloud?
Hadoop
Angular
React
Flask
Explanation - Hadoop is a widely used Big Data framework for distributed processing and storage, often integrated into cloud solutions.
Correct answer is: Hadoop
Q.4 Why is elasticity important for Big Data in the Cloud?
It reduces storage needs
It ensures fixed pricing
It scales resources on demand
It removes data duplication
Explanation - Elasticity in cloud computing allows Big Data applications to handle variable workloads by scaling resources up or down automatically.
Correct answer is: It scales resources on demand
Q.5 Which type of data is typically processed in Big Data analytics?
Structured, Semi-structured, and Unstructured data
Only text data
Only structured data
Only unstructured data
Explanation - Big Data analytics involves all types of data, including structured (databases), semi-structured (JSON/XML), and unstructured (videos, images).
Correct answer is: Structured, Semi-structured, and Unstructured data
Q.6 Which technology enables distributed processing of large datasets in a cloud environment?
MapReduce
Load Balancer
Firewall
VPN
Explanation - MapReduce is a programming model used in Big Data for parallel and distributed processing of large datasets, often deployed in the cloud.
Correct answer is: MapReduce
Q.7 Which of these is a cloud-based Big Data solution from Amazon?
Azure HDInsight
Google BigQuery
Amazon EMR
IBM Watson
Explanation - Amazon Elastic MapReduce (EMR) is a cloud-based service for processing Big Data using Hadoop and Spark.
Correct answer is: Amazon EMR
Q.8 Which of the following is a major challenge in Big Data and Cloud Integration?
Data security
High bandwidth
Low storage costs
Fast provisioning
Explanation - Data security is a primary challenge because Big Data integration in cloud involves large amounts of sensitive information.
Correct answer is: Data security
Q.9 What role does virtualization play in Big Data cloud environments?
Enhances graphic performance
Enables resource pooling and flexibility
Reduces code complexity
Increases latency
Explanation - Virtualization allows multiple virtual resources to be created on physical hardware, making Big Data integration more efficient and scalable.
Correct answer is: Enables resource pooling and flexibility
Q.10 Which of the following is a benefit of Cloud-based Big Data analytics?
Higher upfront hardware costs
Limited accessibility
Global accessibility and scalability
Static data storage
Explanation - Cloud platforms make Big Data analytics globally accessible while ensuring scalability of resources.
Correct answer is: Global accessibility and scalability
Q.11 Which component of Hadoop is responsible for storing large datasets?
MapReduce
HDFS
YARN
Spark
Explanation - Hadoop Distributed File System (HDFS) stores large datasets across clusters, enabling fault tolerance and scalability.
Correct answer is: HDFS
Q.12 What does BigQuery provide in Google Cloud?
File backup
Machine Learning models
Serverless data warehouse for analytics
Virtual private network
Explanation - Google BigQuery is a fully managed, serverless data warehouse optimized for Big Data analytics.
Correct answer is: Serverless data warehouse for analytics
Q.13 In cloud-based Big Data systems, what does 'data velocity' refer to?
Amount of data generated
Speed of data processing
Accuracy of data
Security of data
Explanation - Velocity in Big Data refers to the speed at which new data is generated and needs to be processed in real time or near real time.
Correct answer is: Speed of data processing
Q.14 Which of the following is an open-source Big Data processing engine used in Cloud?
Apache Spark
TensorFlow
Scikit-learn
PyTorch
Explanation - Apache Spark is a distributed Big Data processing engine widely used in cloud environments for faster analytics than Hadoop MapReduce.
Correct answer is: Apache Spark
Q.15 Which type of cloud is preferred for organizations needing strong data privacy in Big Data projects?
Public Cloud
Private Cloud
Community Cloud
Hybrid Cloud
Explanation - Private Cloud ensures greater control and security, making it suitable for sensitive Big Data projects.
Correct answer is: Private Cloud
Q.16 Which cloud provider offers 'HDInsight' for Big Data analytics?
Amazon Web Services
Google Cloud
Microsoft Azure
IBM Cloud
Explanation - Azure HDInsight is a cloud service by Microsoft for Big Data analytics using Hadoop, Spark, and Hive.
Correct answer is: Microsoft Azure
Q.17 Which of these is a common Big Data workload supported by cloud platforms?
Image rendering
Fraud detection
Game development
Web design
Explanation - Fraud detection is a Big Data workload handled effectively on cloud due to high scalability and real-time analytics capabilities.
Correct answer is: Fraud detection
Q.18 Which protocol is commonly used for data transfer in Big Data and Cloud integration?
FTP
HTTP
REST APIs
SMTP
Explanation - REST APIs are widely used in cloud environments for transferring and integrating Big Data services across applications.
Correct answer is: REST APIs
Q.19 Which of these is a challenge in integrating Big Data with multiple clouds?
Interoperability
Data backup
Cost saving
Virtualization
Explanation - Interoperability is a major challenge because different cloud providers use different standards and APIs, complicating Big Data integration.
Correct answer is: Interoperability
Q.20 Which characteristic of Big Data deals with data coming from various sources like social media, sensors, and logs?
Volume
Velocity
Variety
Veracity
Explanation - Variety in Big Data refers to diverse data sources such as structured, semi-structured, and unstructured data.
Correct answer is: Variety
Q.21 What advantage does cloud integration provide for Big Data startups?
Low initial investment
Guaranteed profits
No need for software
Automatic marketing
Explanation - Cloud integration allows startups to use scalable Big Data solutions without investing heavily in infrastructure.
Correct answer is: Low initial investment
Q.22 Which of these cloud deployment models best supports disaster recovery in Big Data systems?
Private Cloud
Public Cloud
Hybrid Cloud
Community Cloud
Explanation - Hybrid Cloud provides redundancy by combining private and public clouds, making it ideal for disaster recovery in Big Data systems.
Correct answer is: Hybrid Cloud
Q.23 Which Big Data term refers to uncertainty in data quality?
Volume
Veracity
Variety
Velocity
Explanation - Veracity refers to the trustworthiness and quality of data, which is crucial in Big Data analytics.
Correct answer is: Veracity
Q.24 Which storage system is commonly used in cloud for handling Big Data?
Relational databases
NoSQL databases
Flat files
Spreadsheets
Explanation - NoSQL databases like MongoDB and Cassandra are preferred in cloud Big Data solutions due to scalability and flexibility.
Correct answer is: NoSQL databases
Q.25 What is the main reason for using Spark over MapReduce in cloud Big Data systems?
Better visualization
Real-time data processing
Low bandwidth usage
Lower storage costs
Explanation - Apache Spark is chosen over MapReduce because it supports real-time processing, unlike MapReduce which is batch-oriented.
Correct answer is: Real-time data processing