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Welcome to the Economics of Big Data MCQs Page

Dive deep into the fascinating world of Economics of Big Data with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Economics of 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 Economics of 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 Economics of 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 Economics of Big Data. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Economics of Big Data MCQs | Page 3 of 6

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Q21.
What is identified as one of the major bottlenecks in the adoption of Big Data technologies?

a.

Inadequate data volume

b.

Insufficient technology advancements

c.

Lack of analytical competence and skills

d.

Excessive data complexity

Discuss
Answer: (c).Lack of analytical competence and skills Explanation:One of the major bottlenecks in the adoption of Big Data technologies is the lack of analytical competence and skills.
Q22.
According to McKinsey, how many experts in the area of Big Data analytics will the US market demand by 2018?

a.

4 million

b.

2.5 million

c.

1 million

d.

3 million

Discuss
Answer: (a).4 million Explanation:According to McKinsey, the US market will demand 4 million experts in the area of Big Data analytics by 2018.
Q23.
In which economic area is Big Data analytics expected to play an important role?

a.

Agriculture

b.

Manufacturing

c.

Procurement

d.

Healthcare

Discuss
Answer: (c).Procurement Explanation:Big Data analytics is expected to play an important role in the economic area of procurement.
Q24.
What are some of the areas in the retail sector where added value from Big Data analytics is expected?

a.

Inventory management and product pricing

b.

Agriculture and supply chain optimization

c.

Education and customer service

d.

Healthcare and public relations

Discuss
Answer: (a).Inventory management and product pricing Explanation:Some of the areas in the retail sector where added value from Big Data analytics is expected include inventory management and product pricing.
Q25.
What is the primary purpose of metadata in the context of Big Data and networked environments?

a.

To store and manage large datasets

b.

To conduct complex data analysis

c.

To enable interoperability and information ecosystem control

d.

To create data silos

Discuss
Answer: (c).To enable interoperability and information ecosystem control Explanation:In the context of Big Data and networked environments, the primary purpose of metadata is to enable interoperability and information ecosystem control.
Q26.
What has significantly changed the nature and importance of metadata in the context of the World Wide Web?

a.

The emergence of data silos

b.

The decline of research in metadata issues

c.

The broadening of research areas in Library and Information Sciences

d.

The shift from complex methodologies to application-oriented approaches

Discuss
Answer: (d).The shift from complex methodologies to application-oriented approaches Explanation:The nature and importance of metadata in the context of the World Wide Web has significantly changed due to the shift from complex methodologies to more application-oriented approaches.
Q27.
What are the Linked Data principles primarily focused on?

a.

Data storage and retrieval

b.

Semantic metadata integration and reutilization

c.

Data security in networked environments

d.

Data analytics for decision support

Discuss
Answer: (b).Semantic metadata integration and reutilization Explanation:The Linked Data principles are primarily focused on semantic metadata integration and reutilization.
Q28.
What is one of the key benefits of the Linked Data approach?

a.

It discards unstructured data.

b.

It focuses on document-based resources.

c.

It supports interoperability and data portability.

d.

It is based on proprietary standards.

Discuss
Answer: (c).It supports interoperability and data portability. Explanation:One of the key benefits of the Linked Data approach is that it supports interoperability and data portability.
Q29.
What does the Linked Data approach use to establish links between entities identified by different namespaces?

a.

RDF data model

b.

URLs

c.

IRIs

d.

RDF vocabularies

Discuss
Answer: (c).IRIs Explanation:The Linked Data approach uses IRIs (Internationalized Resource Identifiers) to establish links between entities identified by different namespaces.
Q30.
What is one of the advantages of timeliness associated with publishing and updating Linked Data

a.

It requires complex extraction, transformation, and loading processes.

b.

It enables easy integration of different Linked Data sets.

c.

It results in significant delays in accessing updated data.

d.

It is based on proprietary mechanisms for representing information.

Discuss
Answer: (b).It enables easy integration of different Linked Data sets. Explanation:One of the advantages of timeliness associated with publishing and updating Linked Data is that it enables easy integration of different Linked Data sets.
Page 3 of 6

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