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Data Virtualization

Data integration approach

5 minutes 5 Questions

Data Virtualization is a data integration approach that allows applications to access and query data across multiple disparate sources without moving or copying the physical data. It creates an abstraction layer that presents data from various sources as if it were from a single virtual database. …

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Big Data Engineer - Data Virtualization Example Questions

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Question 1

What is the primary advantage of using Data Virtualization?

Increased data accuracy Real-time access to data Better data security Improved data governance Faster data processing Lower data storage costs

Correct Answer: Real-time access to data

One of the primary advantages of using Data Virtualization is the ability to gain real-time access to data from disparate sources without having to physically integrate the data. This enables faster decision-making and more efficient use of data.

Question 2

What is the main challenge of performing Data Virtualization on unstructured data?

Unstructured data is too large to virtualize effectively The main challenge of performing Data Virtualization on unstructured data is that unstructured data often lacks the metadata required for effective virtualization Virtualizing unstructured data is no different than virtualizing structured data Virtualizing unstructured data can lead to data loss or corruption The technology required to virtualize unstructured data is too expensive

Correct Answer: The main challenge of performing Data Virtualization on unstructured data is that unstructured data often lacks the metadata required for effective virtualization

The main challenge of performing Data Virtualization on unstructured data is the lack of metadata. Unstructured data is often composed of files or documents that may lack the underlying structure of a relational database, and thus may not have the metadata required for effective virtualization. This can be overcome by using advanced techniques like machine learning to automatically classify and tag unstructured data.

Question 3

What is the process of combining data from different sources into a physical integrated view called?

Data Federation Data Merging Data Integration Data Staging Data Accumulation Data Normalization

Correct Answer: Data Integration

Data integration refers to the process of combining data from different sources into a physical integrated view. This is different from data federation, which involves combining data from different sources into a virtualized view without physically integrating the data.

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