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Data Virtualization: Better than Integration by ETL or Data WareHouses
By now you’ve heard of virtualization when applied to servers. Server virtualization is the primary enabling technology for cloud computing. Forrester Research and others are now talking about another kind of virtualization that has potential to further transform IT operations — data virtualization.
Data virtualization is a single interface for accessing data that originates from many different application and storage locations. The underlying data may be stored on different servers and storage devices, each of which may be exposed by different access methods, APIs or query languages. Data virtualization can aggregate and combine data from the many different sources and can process and transform it so that it can be consistently accessed. Data virtualization technology can form the core of data integration, business intelligence, service-oriented architecture data services, cloud computing, master data management and enterprise search initiatives.
The Forrester report finds that Data Virtualization is becoming increasingly popular and it competes well against traditional techniques used for data integration. Data integration based on techniques like ETL (extract/transform/load) and data warehousing (DB consolidation) are often slow, complex, expensive and result in the loss of some information.
Forrester finds like less than 20 percent of IT organizations have adopted some form of data virtualization, but it expects that number to grow rapidly over the next 18 to 36 months. Brian Hopkins, author of the Forrester report, said that “we expect this market attitude to change as technology advancement, more third-party integration, and new usage patterns lead to increasing awareness of data virtualisation’s potential.”
