Data virtualization

Data Virtualization has emerged as the new technology to complete the virtualization stack in the enterprise. The virtualization stack can be divided into the following categories or technology layers: server infrastructure (memory and CPU), network resources, applications layer and finally the data layer. The Data Virtualization is designed to combine disparate data silos into a single uniform data source and make the data available to consuming applications. The challenges DV addresses were present in the enterprise for a long time: uniform holistic access, data access security, performance and political and cultural barriers of the data owners forcing them to share the data they own and responsible for. Several other technologies were designed to solve them in past: Master Data Management (MDM), Data Warehouse solutions, Data Extract Transform and Load technologies (ETL), Data Aggregation. With the advent of cloud computing, DV technology was designed to utilize the advantages of cloud platform and resolve the above problems in more effective and efficient way than older traditional technologies.