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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 3 of 43

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Q21.
Which layer of the technology stack provides the infrastructure for storage, access, and management of Big Data?

a.

Foundational layer

b.

Analytics layer

c.

Applications layer

d.

Stream processing layer

Discuss
Answer: (a).Foundational layer Explanation:The foundational layer provides the infrastructure for storage, access, and management of Big Data.
Q22.
What are the potential solutions for storing and accessing Big Data in response to upper-layer requests?

a.

Stream processing solutions

b.

Cloud infrastructures

c.

Distributed persistent storage

d.

All of the above

Discuss
Answer: (d).All of the above Explanation:Depending on the nature of data, stream processing solutions, distributed persistent storage, cloud infrastructures, or combinations of these may be used for storing and accessing Big Data.
Q23.
What is the primary focus of the analysis of the state of development of Big Data technologies?

a.

Foundational layer improvements

b.

Analytics layer advancements

c.

Semantics-based processing

d.

Application layer enhancements

Discuss
Answer: (c).Semantics-based processing Explanation:The primary focus of the analysis is semantics-based processing in Big Data technologies.
Q24.
Which layer of the technology stack deals with storage, access, and management of Big Data?

a.

Foundational layer

b.

Analytics layer

c.

Applications layer

d.

Semantic layer

Discuss
Answer: (a).Foundational layer Explanation:The foundational layer of the technology stack deals with storage, access, and management of Big Data.
Q25.
Which layer of the Big Data processing technology stack is responsible for analytics?

a.

Foundational layer

b.

Applications layer

c.

Semantic layer

d.

Middle layer

Discuss
Answer: (d).Middle layer Explanation:The middle layer of the technology stack is responsible for analytics.
Q26.
What is the primary functionality of focused applications or services at the top of the Big Data processing stack?

a.

Data warehousing

b.

Extracting correlations

c.

Providing generic technologies

d.

Offering specialized services to end users

Discuss
Answer: (d).Offering specialized services to end users Explanation:Focused applications or services at the top of the stack offer specialized services to end users based on lower-layer technologies.
Q27.
What is the primary concern of the foundational layer in Big Data processing?

a.

Processing data efficiently

b.

Processing data with high complexity

c.

Processing data with high velocity

d.

Processing large volumes of data as soon as possible

Discuss
Answer: (d).Processing large volumes of data as soon as possible Explanation:The foundational layer is primarily concerned with processing large volumes of data as soon as possible.
Q28.
Why are hybrid infrastructures used in Big Data processing?

a.

To achieve higher complexity in data analysis

b.

To balance processing efficiency aspects for volume and velocity

c.

To decrease the variety of data sources

d.

To simplify the data representation

Discuss
Answer: (b).To balance processing efficiency aspects for volume and velocity Explanation:Hybrid infrastructures are used to balance processing efficiency aspects for volume and velocity in Big Data processing.
Q29.
What is the major conceptual complication for analytics?

a.

Complexity is correlated with effectiveness.

b.

Variety is correlated with efficiency.

c.

Efficiency is correlated with complexity.

d.

Efficiency is anticorrelated to effectiveness.

Discuss
Answer: (d).Efficiency is anticorrelated to effectiveness. Explanation:The major conceptual complication for analytics is that efficiency is anticorrelated to effectiveness.
Q30.
What is the focus of the 7th Framework Programme (FP7) in the field of Big Data Computing?

a.

Semantics-based processing

b.

Intelligent Information Management (IIM)

c.

Information extraction and prediction

d.

Machine translation and ontology development

Discuss
Answer: (b).Intelligent Information Management (IIM) Explanation:Big Data processing, including semantics, is addressed by the strategic objective of Intelligent Information Management (IIM) within the 7th Framework Programme (FP7).
Page 3 of 43

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