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In the context of a Lakehouse architecture, data virtualization plays a pivotal role in enhancing data access and integration. Considering a scenario where a multinational corporation operates across various regions with disparate data sources, including transactional databases, CRM systems, and social media platforms, the corporation aims to achieve a unified view of its data for real-time analytics and decision-making. The IT team is evaluating the best approach to integrate these data sources without incurring high costs associated with data movement or duplication. Which of the following statements accurately describes the concept of data virtualization in this Lakehouse architecture and its benefits? Choose the best option.
A
Data virtualization in a Lakehouse architecture is not applicable as it only supports data stored within the data lake, making it unsuitable for integrating external data sources.
B
Data virtualization involves the physical consolidation of all data sources into a single repository within the Lakehouse, ensuring data is always up-to-date but at a higher storage cost.
C
Data virtualization creates a virtual layer that abstracts the underlying data sources, enabling seamless access and integration without the need for physical data movement, thus reducing costs and improving efficiency.
D
Data virtualization is primarily used for data backup and recovery purposes in a Lakehouse architecture, with minimal impact on data access or integration capabilities.