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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 40 of 43

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Q391.
What is important in terms of data access for rendering, representation, and navigation of results in various domains?

a.

Custom interfaces

b.

Concurrent access

c.

Data consistency

d.

Data rendering compliance

Discuss
Answer: (a).Custom interfaces Explanation:Custom interfaces are important for data access in terms of rendering, representation, and navigation of results in various domains.
Q392.
Which domain requires concurrent access and data consistency?

a.

Health and scientific research

b.

Social media and smart cities

c.

Financial data and health care

d.

Educational and cultural heritage

Discuss
Answer: (a).Health and scientific research Explanation:Health and scientific research require concurrent access and data consistency.
Q393.
What feature may be strongly desirable for scientific and research applications, financial data, and health care?

a.

Complex data processing

b.

Fast indexing

c.

Data rendering compliance

d.

Faceted query results

Discuss
Answer: (c).Data rendering compliance Explanation:Flexible visual rendering (distributions, pies, histograms, trends, etc.) may be strongly desirable for scientific and research applications, financial data, and health care.
Q394.
In which domains can faceted query results be very interesting?

a.

Scientific and research

b.

Financial data and health care

c.

Educational and cultural heritage

d.

Social media and smart cities

Discuss
Answer: (c).Educational and cultural heritage Explanation:Faceted query results can be very interesting for navigating in mainly text-based Big Data, as in educational and cultural heritage application domains.
Q395.
When is fast indexing most relevant in different domains?

a.

When a huge amount of small data needs to be collected

b.

When data processing is the primary goal

c.

When semantic data structures are used

d.

When complex and deep data processing is required

Discuss
Answer: (a).When a huge amount of small data needs to be collected Explanation:Fast indexing is most relevant in different domains when a huge amount of small data needs to be collected and accessed quickly.
Q396.
What approach may be suitable for contexts requiring complex and deep data processing?

a.

Usage of HDFS

b.

Usage of ontologies and RDF databases

c.

Fast indexing

d.

Custom interfaces

Discuss
Answer: (b).Usage of ontologies and RDF databases Explanation:The usage of ontologies and RDF databases may be suitable for contexts requiring complex and deep data processing.
Q397.
In which applications is the possibility of supporting statistical and logical analyses on data via specific queries and reasoning important?

a.

Scientific research and education

b.

Social media and networking

c.

Health care and finance

d.

Smart cities and security

Discuss
Answer: (b).Social media and networking Explanation:The possibility of supporting statistical and logical analyses on data via specific queries and reasoning is important in applications like social media and networking.
Q398.
In which contexts is the continuous processing of data streams particularly important?

a.

Scientific research and education

b.

Health care and finance

c.

Smart cities and security

d.

Social media and networking

Discuss
Answer: (c).Smart cities and security Explanation:The continuous processing of data streams is particularly important in contexts like smart cities and security.
Q399.
Which approach is based on complex event processing (CEP) and improves the speed of analysis in real-time monitoring?

a.

Active query

b.

Batch processing

c.

Data warehousing

d.

Data mining

Discuss
Answer: (a).Active query Explanation:Complex event processing (CEP) based on active query improves the speed of analysis in real-time monitoring.
Q400.
In which domains is the speed of analysis not a primary feature?

a.

Health care and finance

b.

Social media and networking

c.

Scientific research and education

d.

Smart cities and security

Discuss
Answer: (c).Scientific research and education Explanation:The speed of analysis is not a primary feature in the domains of scientific research and education.
Page 40 of 43

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