How many V's of Big Data?
2
3
4
5
Correct Answer :
D. 5
There are five V's of big data; these are Volume, Velocity, Variety, Value and Veracity. Knowing the 5 V's enables data scientists to extract more value from their data while also enabling the scientists' organizations to become more customer-centric as a result of their knowledge.
Related Questions
The _______ is the default partitioned in Hadoop, and it offers a method called getPartition that allows us to partition data.
HashPartitioner
Map function
Reduce function
All of the mentioned above
Analytics has begun to impact almost every industry including,
Healthcare,
Education and telecom
Telecom
All of the mentioned above
MongoDB support cross platform and is written in _____ language.
Python
C++
R
Java
A _____ serves as the master, and each cluster has just one NameNode.
Data Node
Block Size
Data block
NameNode
Effective _____ prescriptive data tools can help businesses using informed data to create the processes and for managing and analyzing data anytime and anywhere.
Cloud-based
Data warehouse
System ingestion
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
MongoDB is a ____ database.
SQL
DBMS
NoSQL
RDBMS
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
______ 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
Security infrastructure refers the data about your constituents needs to be protected to ____.
Meet compliance requirements
Protect the privacy
Both A and B
None of the mentioned above
To automate the big data solutions like workflows, we use _____ technology.
Orchestration
HBase
HDFS
None of the mentioned above
Which of the following are Benefits of Big Data Processing?
Cost Reduction
Time Reductions
Smarter Business Decisions
All of the mentioned above
Amongst which of the following is / are correct,
Hive is a relational database that supports SQL queries.
Pig is a relational database that supports SQL queries.
Both A and B
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
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 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
______ involves the simultaneous execution of multiple sub-tasks that collectively comprise a larger task.
Parallel data processing
Single channel processing
Multi data processing
None of the mentioned above
_____ is the supporting physical infrastructure is fundamental to the operation and scalability of big data architecture.
Redundant physical infrastructure
Integrated System
Integrated Database
All of the mentioned above
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
Amongst which of the following is / are the examples of descriptive analytics,
Traffic and Engagement Reports
Financial Statement Analysis
Demand Trends and Aggregated Survey Results
All of the mentioned above
____ is also known as Hosted Hypervisor.
TYPE-1 Hypervisor
TYPE- 2 Hypervisor
Both A and B
None of the mentioned above
Prescriptive analytics is a process that _____ and provides instant recommendations on how to optimize business practices.
Analyzes data
Data storage
Data ingestion
None of the mentioned above
An ____ consisted of highly structured data managed by the line of business in a relational database.
Operational data source
Qualitative data source
Both A and B
None of the mentioned above
_____ is a form of interactive data exploration by data scientists or data analysts.
Data and storage
Analysis and reporting
System and development
None of the mentioned above
The weight of a machine is a,
Discrete variable
Quantitative variable
Qualitative variable
Superlative variable
Database requirements for operational data includes ___.
Indexing and Cataloging, Replication
File Storage and Structure, Query Processing
Transactions Support
All of the mentioned above
Amongst which of the following is / are true with reference to predictive modeling,
A tool used in predictive analytics
A process that uses data mining and statistics to develop models
Examine current and historical datasets for underlying patterns
All of the mentioned above
Descriptive analytics is a statistical method that is used to search and summarize ____ in order to identify patterns or meaning.
Account data
Historical data
Financial data
None of the mentioned above
Amongst which of the following is/are the cloud deployment models,
Public Cloud
Private Cloud
Hybrid Cloud
All of the mentioned above
Variety describes one of the biggest challenges of ______.
Big data
Data science
Data integration
None of the mentioned above