Google Cloud Professional Data Engineer Practice Exam 2025 – Complete Preparation

Data virtualization refers to the process that enables access to data without the need for it to be physically moved or replicated in storage. This capability is particularly valuable in data engineering as it facilitates the integration and management of data from multiple sources in real time. By presenting a unified view of data from disparate systems, data virtualization allows data engineers and analysts to perform queries and generate insights efficiently without the overhead associated with data migration or duplication.

The essence of data virtualization lies in its ability to abstract the underlying data sources, letting users access and manipulate data as if it were all stored in a single repository. This not only improves performance but also accelerates the development of data-driven applications and analytics.

While real-time data analysis is a potential benefit of data virtualization, it is primarily the functionality of accessing data without physical movement that distinctly characterizes data virtualization. Additionally, creating physical backups of data is unrelated to the concept of virtualization, as it involves duplicating the data itself rather than merely accessing it. Finally, limiting storage to local data contradicts the core idea of data virtualization, which thrives on accessing remote and potentially diverse data sources.