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Welcome to the Introduction to Big Data MCQs Page

Dive deep into the fascinating world of Introduction to Big Data with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Introduction to Big Data, a crucial aspect of Big Data Computing. In this section, you will encounter a diverse range of MCQs that cover various aspects of Introduction to Big Data, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Big Data Computing.

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Check out the MCQs below to embark on an enriching journey through Introduction to Big Data. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Big Data Computing.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Introduction to Big Data. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Introduction to Big Data MCQs | Page 22 of 43

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Q211.
What is the purpose of identifying the main features that characterize architectures for solving Big Data problems?

a.

To discourage the use of Big Data technologies

b.

To create competition among technical staff

c.

To help orient technical staff in choosing solutions

d.

To eliminate the need for data analytics

Discuss
Answer: (c).To help orient technical staff in choosing solutions Explanation:Identifying these features helps technical staff choose appropriate solutions.
Q212.
Why are some features of Big Data solutions dependent on architecture and infrastructure facilities?

a.

To limit the capabilities of Big Data solutions

b.

To increase the complexity of Big Data solutions

c.

To take advantage of the flexibility of the infrastructure

d.

To discourage the use of cloud-based solutions

Discuss
Answer: (c).To take advantage of the flexibility of the infrastructure Explanation:Some features of Big Data solutions depend on the architecture and infrastructure facilities to take advantage of their flexibility.
Q213.
Where can specific Big Data solutions and techniques inherit/exploit capabilities?

a.

From external vendors

b.

From the cloud

c.

From proprietary databases

d.

From the operating system

Discuss
Answer: (d).From the operating system Explanation:Specific Big Data solutions and techniques can inherit/exploit capabilities from the operating system.
Q214.
What does the term "scalability" refer to in the context of Big Data solutions?

a.

The ability to process small data sets efficiently

b.

The ability to maintain consistent performance with varying data sizes

c.

The ability to perform operations sequentially on large data sets

d.

The ability to minimize the use of distributed architectures

Discuss
Answer: (b).The ability to maintain consistent performance with varying data sizes Explanation:Scalability in Big Data solutions refers to the ability to maintain consistent performance regardless of varying data sizes.
Q215.
How is scalability typically achieved in Big Data solutions?

a.

By using sequential processing algorithms

b.

By using expensive hardware resources

c.

By adopting distributed and/or parallel architectures

d.

By limiting data collection and processing

Discuss
Answer: (c).By adopting distributed and/or parallel architectures Explanation:Scalability in Big Data solutions is typically achieved by adopting distributed and/or parallel architectures.
Q216.
What is one approach to optimizing computational scalability in Big Data solutions?

a.

Using traditional computational algorithms

b.

Restructuring algorithms for scalability

c.

Avoiding parallel and distributed architectures

d.

Reducing the size of data sets

Discuss
Answer: (b).Restructuring algorithms for scalability Explanation:Optimizing computational scalability in Big Data solutions often involves restructuring algorithms to make them scalable.
Q217.
Why is it challenging to determine the scalability of a storage solution for large experiments?

a.

Because storage size and cost are always predictable

b.

Because large experiments don't require scalable storage

c.

Because data collection and processing may not be predictable in the long term

d.

Because storage needs for large experiments are always fixed

Discuss
Answer: (c).Because data collection and processing may not be predictable in the long term Explanation:It's challenging to determine the scalability of a storage solution for large experiments because data collection and processing may not be predictable in the long term.
Q218.
What is the suggested approach for dealing with the need for increased storage space in the face of uncertainty?

a.

Use a predictive model to precisely estimate storage needs

b.

Work with cheap hardware and increase storage on demand

c.

Limit the amount of data collected in large experiments

d.

Rely on traditional RDBMS for storage

Discuss
Answer: (b).Work with cheap hardware and increase storage on demand Explanation:The suggested approach is to work with cheap hardware and increase storage on demand when needed, rather than relying on a predictive model for precise estimates.
Q219.
What is a multitiered storage system in the context of optimizing reaction time and scalability?

a.

A system with a single storage medium to reduce costs

b.

A system with multiple layers of storage media with different response times and costs

c.

A system with no storage hierarchy

d.

A system with unlimited storage capacity

Discuss
Answer: (b).A system with multiple layers of storage media with different response times and costs Explanation:A multitiered storage system consists of multiple layers of storage media with different response times and costs.
Q220.
How does a multitiered storage system contribute to optimizing reaction time and scalability?

a.

By using a single layer of storage media for all data

b.

By implementing all layers of the memory hierarchy

c.

By passing data from one storage layer to another based on access velocity

d.

By eliminating the need for cache memories

Discuss
Answer: (c).By passing data from one storage layer to another based on access velocity Explanation:A multitiered storage system optimizes reaction time and scalability by passing data from one storage layer to another based on access velocity.
Page 22 of 43

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