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Welcome to the Linked Data in Enterprise Integration MCQs Page

Dive deep into the fascinating world of Linked Data in Enterprise Integration with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Linked Data in Enterprise Integration, a crucial aspect of Big Data Computing. In this section, you will encounter a diverse range of MCQs that cover various aspects of Linked Data in Enterprise Integration, 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 Linked Data in Enterprise Integration. 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 Linked Data in Enterprise Integration. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Linked Data in Enterprise Integration MCQs | Page 4 of 11

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Q31.
What are the two distinct areas in an enterprise where search technology needs to be applied?
Discuss
Answer: (a).Internal search and external search Explanation:The two distinct areas in an enterprise where search technology needs to be applied are internal search (for employees) and external search (for customers and the public).
Q32.
What is the primary challenge when integrating relational data into Linked Data in an enterprise context?
Discuss
Answer: (a).Query performance and scalability Explanation:The primary challenge when integrating relational data into Linked Data in an enterprise context is query performance and scalability.
Discuss
Answer: (b).It avoids the higher deployment costs associated with data duplication. Explanation:SparqlMap helps avoid the higher deployment costs associated with data duplication when integrating relational data into Linked Data.
Q34.
What does the standardization of the RDB to RDF Mapping Language (R2RML) by the W3C RDB2RDF Working Group establish?
Discuss
Answer: (b).Interoperable ecosystem of tools Explanation:The standardization of the RDB to RDF Mapping Language (R2RML) by the W3C RDB2RDF Working Group establishes an interoperable ecosystem of tools for mapping relational data to RDF.
Q35.
Why is it important to have granular access control mechanisms in the context of enterprise data integration?
Discuss
Answer: (c).To ensure the security of integrated data Explanation:Granular access control mechanisms are important in the context of enterprise data integration to ensure the security of integrated data and control who has access to it.
Discuss
Answer: (d).To manage user identities for authentication Explanation:Single sign-on (SSO) solutions are crucial for large enterprises to manage user identities for authentication across a large number of web-based applications.
Discuss
Answer: (c).A Linked Data-based approach for SSO Explanation:WebID is a Linked Data-based approach for single sign-on (SSO) solutions.
Discuss
Answer: (b).Enriching and interlinking identities with background knowledge Explanation:When transferring user identities to the Enterprise Data Web for a WebID-based SSO solution, a challenge is to enrich and interlink identities with background knowledge while maintaining privacy.
Q39.
What is the primary goal of distributed group management and authorization in the context of SSO solutions for large enterprises?
Discuss
Answer: (d).Ensuring that company-wide policies are enforced Explanation:The primary goal of distributed group management and authorization in the context of SSO solutions for large enterprises is to ensure that company-wide policies are enforced.
Discuss
Answer: (a).ETL requires the fusion of knowledge bases, while Linked Data integration often does not. Explanation:The main difference is that the ETL (extract-transform-load) paradigm requires the fusion of knowledge bases, while Linked Data integration often does not require fusion.

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