What is Data Virtualization

Definition

Data virtualization is an integration approach that provides a unified, queryable view of data from multiple sources without physically moving or copying it, letting users access and combine distributed data in real time as if it were in a single store.

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Provides unified access to many sources without copying or moving data
Delivers real-time results that reflect the current state of source systems
Reduces storage and ETL cost by querying data in place
Speeds delivery of integrated views without building new physical pipelines

Real World Example

An insurer uses data virtualization to present underwriters a single view that joins live data from policy, claims, and external risk systems on demand, without first copying all that data into a warehouse.

FAQs

How does data virtualization differ from ETL?

ETL physically copies and consolidates data, while virtualization leaves data in place and queries it live through a unified abstraction layer.

What are the benefits of virtualization?

Real-time access, no data duplication, lower storage cost, and faster delivery of integrated views.

What are its limitations?

Query performance depends on the source systems, and heavy virtualized queries can strain live operational databases.