MCQ Collection
Big Data Analytics MCQs
Practice Big Data Analytics questions with answers and explanations.
Choose an option to check your answer.
A.
Veracity
B.
Velocity
C.
Value
D.
Volume
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Correct Answer: A. Veracity
Explanation:
Veracity reflects the trustworthiness and quality of data.
Cleaning, validation, and provenance help manage this challenge.
Choose an option to check your answer.
A.
Variety
B.
Value
C.
Volume
D.
Volatility
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Correct Answer: B. Value
Explanation:
Value concerns whether analysis leads to meaningful decisions or benefits.
Large data alone is not useful unless it supports a real objective.
Choose an option to check your answer.
A.
Adding more memory to one machine only
B.
Reducing the number of data partitions
C.
Adding more machines to distribute storage or computation
D.
Replacing distributed processing with manual analysis
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Correct Answer: C. Adding more machines to distribute storage or computation
Explanation:
Horizontal scaling expands a cluster by adding nodes.
It is a core design principle of many Big Data platforms.
Choose an option to check your answer.
A.
Adding more cluster nodes
B.
Dividing data into more files only
C.
Replicating every record across the internet
D.
Increasing the resources of a single machine
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Correct Answer: D. Increasing the resources of a single machine
Explanation:
Vertical scaling upgrades CPU, memory, or storage on one server.
It is simpler but eventually reaches hardware and cost limits.
Choose an option to check your answer.
A.
Each node has its own processor, memory, and storage and communicates over a network
B.
All nodes use one central memory bus
C.
Every node stores only metadata
D.
The system runs on a single mainframe
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Correct Answer: A. Each node has its own processor, memory, and storage and communicates over a network
Explanation:
Shared-nothing systems avoid a single shared hardware bottleneck.
They scale by partitioning data and work across independent nodes.
Choose an option to check your answer.
A.
It guarantees perfect data quality
B.
Moving computation near the data reduces network transfer
C.
It removes the need for replication
D.
It converts unstructured data into tables
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Correct Answer: B. Moving computation near the data reduces network transfer
Explanation:
Large datasets are expensive to move across a network.
Scheduling computation where blocks already reside improves efficiency.
Choose an option to check your answer.
A.
No component can ever fail
B.
All tasks must run on one machine
C.
The system can continue operating despite some component failures
D.
Every record is processed exactly once automatically
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Correct Answer: C. The system can continue operating despite some component failures
Explanation:
Commodity hardware failures are expected in large clusters.
Replication, retries, and recovery mechanisms preserve service.
Choose an option to check your answer.
A.
A single database table
B.
A collection of chart categories
C.
A compression format
D.
A group of networked machines working together
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Correct Answer: D. A group of networked machines working together
Explanation:
Cluster nodes cooperate to store data and execute distributed tasks.
The cluster appears as a larger computing platform.
Choose an option to check your answer.
A.
Coordinating computation across multiple networked machines
B.
Running every task in one process
C.
Storing data only in spreadsheets
D.
Using a single CPU core
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Correct Answer: A. Coordinating computation across multiple networked machines
Explanation:
Distributed computing divides work among nodes and combines their results.
It enables scale and resilience beyond one machine.
Choose an option to check your answer.
A.
Processing one record after another only
B.
Executing multiple operations at the same time
C.
Copying files without computation
D.
Serializing every task onto one thread
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Correct Answer: B. Executing multiple operations at the same time
Explanation:
Parallelism reduces completion time by using multiple processing units concurrently.
Distributed systems often combine parallelism with data partitioning.
Choose an option to check your answer.
A.
Interactive animation
B.
Single-record manual entry
C.
Batch processing
D.
Real-time gaming graphics
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Correct Answer: C. Batch processing
Explanation:
Batch systems process bounded collections of data in large jobs.
They prioritize throughput over immediate response.