Data virtualization delivers a unified, simplified view of an organization’s data that can be accessed anytime. It integrates data from multiple sources, to create a single data layer to support multiple layers and users. The result is faster access to this data, providing instant access, any way you want it.
Data virtualization involves abstracting, transforming, federating and delivering data from disparate sources. This allows users to access the applications without having to know their exact location.
There are some important advantages to data virtualization:
- An organization can gain business insights by leveraging all data
- They can become aware of analytics and business intelligence
- Data virtualization can streamline an organization’s data management approach, which reduces complexity and saves money
Data virtualization involves three key steps. First, data virtualization software is installed on-premise or in the cloud, which collects data from production sources and stays synchronized as those sources change over time. Next, administrators are able to secure, archive, replicate, and transform data using the data virtualization platform as a single point of control. Last, it allows users to provision virtual copies of the data that consume significantly less storage than physical copies.
Some use cases for data virtualization are:
- Application development
- Backup and disaster recovery
- Datacenter migration
- Test data management
- Packaged application projects