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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 5 of 43

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Q41.
Which project integrates personal data in a user-controlled personal service for intelligent personal information management?

a.

Digital.me

b.

Fish4Knowledge

c.

iProd

d.

Teleios

Discuss
Answer: (a).Digital.me Explanation:The Digital.me project integrates personal data in a user-controlled personal service for intelligent personal information management.
Q42.
What is the goal of the Fish4Knowledge project?

a.

Developing a specialized query system for fish monitoring

b.

Reducing video data by 10 × 1015 pixels

c.

Developing machine- and human-accessible vocabularies for describing fish

d.

Creating a data model for fish species

Discuss
Answer: (c).Developing machine- and human-accessible vocabularies for describing fish Explanation:The goal of the Fish4Knowledge project is to develop machine- and human-accessible vocabularies for describing fish.
Q43.
What is the primary focus of the Render project?

a.

Developing a decision support platform for logistics operations

b.

Investigating the aspect of diversity of Big Data semantics

c.

Establishing a sustainable European community of researchers

d.

Creating a workbench of interoperable services for decision-making

Discuss
Answer: (b).Investigating the aspect of diversity of Big Data semantics Explanation:The primary focus of the Render project is investigating the aspect of diversity of Big Data semantics.
Q44.
Which project works toward establishing a sustainable European community of researchers and develops technologies for handling data purposefully at scale?

a.

LATC

b.

PlanetData

c.

Advance

d.

Cubist

Discuss
Answer: (b).PlanetData Explanation:The PlanetData project works toward establishing a sustainable European community of researchers and develops technologies for handling data purposefully at scale.
Q45.
What is the main goal of the LATC project?

a.

Creating a decision support platform for logistics operations

b.

Establishing a virtual laboratory for research and experimentation

c.

Publishing European governmental data as Linked Data on the Web

d.

Developing a platform for data federation and semantic data warehousing

Discuss
Answer: (c).Publishing European governmental data as Linked Data on the Web Explanation:The main goal of the LATC project is to publish European governmental data as Linked Data on the Web and interlink it with other governmental data.
Q46.
Which project focuses on developing a workbench of interoperable services for scalable text and opinion mining, collaboration support, and decision-making support?

a.

Promise

b.

Dicode

c.

Cubist

d.

iProd

Discuss
Answer: (b).Dicode Explanation:The Dicode project focuses on developing a workbench of interoperable services for scalable text and opinion mining, collaboration support, and decision-making support.
Q47.
What is the primary concern when dealing with data at the foundational layer of the Big Data processing stack?

a.

Achieving better collaboration in large-scale collaborative projects

b.

Processing data in a timely fashion

c.

Handling data complexity and variety

d.

Processing data as fast as possible

Discuss
Answer: (d).Processing data as fast as possible Explanation:The primary concern at the foundational layer is processing as much data as possible (volume) and as soon as possible (velocity).
Q48.
Which project focuses on developing a user-controlled personal service for intelligent personal information management?

a.

Fish4Knowledge

b.

Teleios

c.

Digital.me

d.

Promise

Discuss
Answer: (c).Digital.me Explanation:The Digital.me project focuses on developing a user-controlled personal service for intelligent personal information management.
Q49.
What is the main goal of the Tridec project?

a.

Developing a decision support platform for logistics operations

b.

Creating a workbench of interoperable services for data-intensive applications

c.

Supporting human experts in decision processes for emergency situations

d.

Elaborating a data model and query language for Earth Observation images

Discuss
Answer: (c).Supporting human experts in decision processes for emergency situations Explanation:The main goal of the Tridec project is to support human experts in decision processes for emergency situations triggered by the earth system in complex and time-critical settings.
Q50.
Which project investigates methods and techniques for leveraging diversity as a source of innovation and creativity in Big Data?

a.

PlanetData

b.

Robust

c.

Dicode

d.

Render

Discuss
Answer: (d).Render Explanation:The Render project investigates methods and techniques for leveraging diversity as a source of innovation and creativity in Big Data.
Page 5 of 43

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