Data Virtualization in Data Integration
Data virtualization is a method of data integration that enables to gather data contained within a variety of databases in a single virtual warehouse. The process of data virtualization includes four major steps:
- Organizing software interfaces to understand the structure of data sources and their level of security.
- Bringing these data structures to a single data integration solution for viewing and administration.
- Establishing a true metadata abstraction layer, which can be used for data organization, data management, data quality control, etc.
- Synchronize the data across the various sources.
Data virtualization combines various data warehouses into a single and uniform data source without actually migrating the physical data. This data integration technology has many other business benefits, including:
- Lower costs for physical and virtual data integration
- Maximized agility by avoiding data movement, promoting reuse and ensuring data quality
- Improved security by utilizing an abstraction layer to minimize the impact of change
- Making the data available to various consuming applications: CRM, ERP, Cloud computing platforms, etc.
This positions data virtualization as a powerful data integration technology. It has the required functionality to seamlessly blend various Cloud architectures and on-premises applications. This tremendously simplifies the issues associated with data integration and ongoing data management.