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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 17 of 43

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Q161.
In competitive scenarios among Knowledge Organisms (KOs), who typically acquires a knowledge token?
Discuss
Answer: (a).The KO with the highest fitness. Explanation:In competitive scenarios, the strongest KO, often with the highest fitness, is more likely to acquire the knowledge token.
Discuss
Answer: (c).Providing a capability for data analysis with balanced effectiveness and efficiency. Explanation:The primary objective of a Big Data computing system is to provide a capability for data analysis with balanced effectiveness and efficiency.
Discuss
Answer: (b).They register desired evolutionary changes. Explanation:Ontologies in the KO ecosystem register desired evolutionary changes and are a fundamental part of the ecosystem.
Discuss
Answer: (b).Changes in ontologies are caused by mutagens in incoming data. Explanation:Changes in ontologies are caused by the mutagens brought by incoming data, and they evolve in parallel to data processing.
Discuss
Answer: (c).Describing data about similar things using the same ontological fragments. Explanation:Reuse of an ontology means that data about similar things is described using the same ontological fragments, promoting interoperability.
Discuss
Answer: (a).It reduces the need for excreting knowledge tokens. Explanation:Reuse of ontologies allows for the seamless integration of new knowledge tokens, reducing the need to excrete parts of them.
Discuss
Answer: (c).Mutagens brought by incoming data. Explanation:Changes in ontologies in the evolving KO ecosystem are primarily caused by the mutagens brought by incoming data.
Discuss
Answer: (c).To transform data into knowledge tokens. Explanation:The knowledge extraction subsystem transforms units of data into knowledge tokens in the KO ecosystem.
Discuss
Answer: (c).Through seamless integration of new knowledge tokens. Explanation:Ontologies in the KO ecosystem change naturally through the seamless integration of new knowledge tokens.
Discuss
Answer: (b).The age of assertions in the KO's knowledge body. Explanation:The age of assertions in the KO's knowledge body can influence its fitness.

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