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Data Vitualization: Key to Data Integration Projects?
IDC and Gartner Research tell us that the amount of enterprise information is exploding. In fact, enterprise data doubles every 18 months. That’s a lot of data and the problem is only exacerbated because so much of the data in enterprises is siloed, and the effect of silos is only growing. For example, new collaboration and social media tools are entering the corporate world, but these tools typically are tied to isolated data repositories.
One new technology that tries to improve access to scattered enterprise repositories is called Data Virtualization. It borrows from the service concept used by Service Oriented Architecture (SOA). Content repositories that expose their content as services are being called CaaS (Content as a Service).
And Data Virtualization is the concept of being able to combine data from many disparate CaaS repositories– anywhere across the extended enterprise – in a unified, logically virtualized way for consumption by transactional and business intelligence applications. Many people feel that data virtualization will be a powerful tool when working on data integration projects.
Noel Yuhanna of Forrester Research said that “Data integration is getting harder all the time, and we believe [one of the causes] of that is that data volumes are continuing to grow. [But] you really need data integration because it represents value to the business, to the consumers and to the partners. They want quality data to be able to make better business decisions.”
Data virtualization would seem to be a great tool to improve data accessibility. Improving data quality though may be a more difficult challenge.
