Technology -> Data Management
By: Bloor Research
Published: March 2013
Businesses today have the opportunity to make huge gains by leveraging more data than ever before for both analytics and operations to improve customer service, speed products to market, cut costs and more. They could use lots and lots of data from a growing number of sources that is the good news. That is also the bad news. For data consumers, whether they are end-users or application developers, easy access to relevant data to speed time to market is the key need. For IT serving them, agile data provisioning that is efficient, high-performing and securely managed is the key challenge.
Most organisations have information in various places that they are either unable (perhaps for governance reasons or because the data is incompatible) or unwilling (either for organisational or cost reasons) to consolidate into a single data store. Further, many companies wish to incorporate external data, either from the Internet or from their partner community, into their own environment. Regardless of where it resides, enterprises frequently want to be able to combine this disparate information for a variety of potential reasons that we will come to in a moment. One way to do this is to hardwire links between the various applications and data sources involved and replicate or move data around. However, this is expensive, time consuming and, above all, it is inflexible. An alternative approach is to use data virtualisation, which does not require specifically programmed links and which, as a result, is flexible rather than constrained. In effect, the use of data virtualisation allows the data itself to remain siloed while presenting that data as logically coherent information accessible from a single place.
The term "data virtualisation" might, but should not, be confused with data centre virtualisation except in the sense that both are about the optimisation of resources. Data virtualisation has multiple use cases that extend from business intelligence queries across operational and data warehousing environments, the implementation of registry-based master data management solutions, providing a solution for linking data marts and warehouses into an extended analytic environment, enterprise data sharing (perhaps through data services and including such things as mash-ups), providing infrastructure support for realtime capabilities, and for integrating internal resources with those that may be hosted in SaaS applications, cloud environments, or from the public Internet and open government data initiatives.
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Published by: electronicdawn Ltd.