What is a Virtual Machine (VM)?
Virtual representation of a physical computer
Virtual representation of a logical computer
Virtual System Integration
All of the mentioned above
Correct Answer :
A. Virtual representation of a physical computer
A virtual machine (VM) is a representation of a physical computer that exists only in virtual space. In addition to a CPU, memory, and discs to store your stuff, it is capable of connecting to the internet if necessary. In contrast to the real and tangible components of your computer (referred to as hardware), virtual machines (VMs) are typically conceived of as virtual computers or software-defined computers that run on physical servers and exist solely as code.
Related Questions
The ability to model prices on a variety of factors allows them to make ______ about production, storage, and new discoveries.
No decisions
Better decisions
Unpredictable things
None of the mentioned above
_____ maps input key/value pairs to a set of intermediate key/value pairs.
Reducer
Mapper
File system
All of these
Data Visualization Layer,
To visualize the data
To access the data
To process the data
All of the mentioned above
Amongst which of the following shows an example of unstructured data,
Students roll number, age
Videos
Audio files
Both B and C
Amongst which of the following is/are not Big Data Technologies?
Apache Hadoop
Apache Spark
Apache Kafka
Apache Pytarch
Volume, Velocity and Variety are _____ to Big Data,
Intrinsic
Extrinsic
Both A and B
None of the mentioned above
Amongst which of the following is/are represents the Value of data in Big Data environment,
Worth in information
Useless data
Useless information
None of the mentioned above
Data warehouse modeling is the initial stage of building a data warehouse wherein the ___ is designed.
Schema
Table
Both A and B
None of the mentioned above
_____ hypervisor runs directly on the underlying host system. It is also known as Native Hypervisor or Bare metal hypervisor.
TYPE-1 Hypervisor
TYPE- 2 Hypervisor
Both A and B
None of the mentioned above
Amongst which of the following is / are the goodness of prescriptive analytics,
Exhausting valuable resources on housing data that does not inform business decisions
Spending time sifting through unutilized data sets
Missing out on unique revenue streams and insights
All of the mentioned above
Hadoop is a framework that can be used in conjunction with a number of related products. Among the most common cohorts are ______.
MapReduce, Hive and HBase
Hive, Spark and HBase
Spark, Hive and ZooKeeper
Spark, HBase and Hive
In the given Virtual Architecture, name the missing layer,
Virtualization layer
Storage layer
Abstract layer
None of the mentioned above
______ is best described as a programming model that is used to construct Hadoop-based applications that can be scaled up and down.
Oozie
Zookepper
MapReduce
All of the mentioned above
The database which is used to manage and store data in real time is called ___.
Traditional database
Operational database
Database Management System
None of the mentioned above
Prescriptive analytics utilizes business rules, artificial intelligence, and ____ to simulates various approaches to these numerous outcomes.
Algorithms
Flowchart
System flow
None of the mentioned above
In computers, a ____ is a symbolic representation of facts or concepts from which information may be obtained with a reasonable degree of confidence.
Data
Knowledge
Program
Algorithm
Amongst which of the following is / are the challenge of Big Data processing,
Goes beyond the massive volumes
Increasing velocities of data
Both A and B
None of the mentioned above
______ node serves as the Slave and is responsible for carrying out the Tasks that have been assigned to it by the JobTracker.
TaskReduce
Mapreduce
TaskTracker
JobTracker
Data Query Layer is the _____ where active analytic processing of Big Data takes place.
Architectural layer
Fundamental layer
Backpropogation layer
None of the mentioned above
Scalability is prioritized over latency in jobs such as _____.
HBase
HDFS
Hive
Mapreduce
Predictive analytics is a process harnesses ____, often massive, data sets into models.
Heterogeneous
Storage
Network
None of the mentioned above
In Big Data environment, Veracity of data refers -
Quality or fidelity of data
Large size of the data that cannot be process
Small size of the data that can easily process
All of the mentioned above
MongoDB support cross platform and is written in _____ language.
Python
C++
R
Java
Hypervisors that run several virtual machines on one ____ resources also allow for more efficient utilization,
Physical machine
Abstract machine
System integration
All of the mentioned above
In Big Data environments, Velocity refers
Data can arrive at fast speed
Enormous datasets can accumulate within very short periods of time
Velocity of data translates into the amount of time it takes for the data to be processed
All of the mentioned above
HDFS operates in a ____ manner.
Master-slave architecture
Master-worker architecture
Worker-slave architecture
All of the mentioned above
Amongst which of the following is /are the techniques that are used for predictive analytics,
Linear Regression
Time series analysis and forecasting
Data Mining
All of the mentioned above
Amongst which of the following is / are the correct workflow of predictive analytics,
Import data → Clean the data → Develop a predictive model → Integrate the model
Clean the data → Develop a predictive model → Import data → Integrate the model
Clean the data → Develop a predictive model → Import data → Integrate the model
None of the mentioned above
____ general-purpose model and runtime framework for distributed data analytics.
Mapreduce
Spark
Hive
All of the mentioned above
HDFS stores data in a distributed manner, the data can be processed in parallel on a _____ of nodes.
Cluster
Data Node
Master Node
None of the mentioned above