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Driving Better Outcomes through Workforce Analytics Webcast

Driving Better Outcomes through Workforce Analytics Webcast

Find out what’s really going on in your business...

Legacy Modernization: Look to the Cloud and Open Systems

Legacy Modernization: Look to the Cloud and Open Systems

On the surface, mainframe architecture seems relatively simple: A...

Still keeping your hybrid power systems indoors?  It’s time for change.

Still keeping your hybrid power systems indoors? It’s time for change.

Mobile telecommunications network equipment is expected to work without...

As the Network Changes, Engineers Are Embracing the DevOps Model

As the Network Changes, Engineers Are Embracing the DevOps Model

Businesses that have embraced digital transformation with a clear...

The 5 Most Common Application Bottlenecks

The 5 Most Common Application Bottlenecks

Application bottlenecks can lead an otherwise functional computer or...

Data Virtualization and Big Data Business Intelligence

November 11, 2011 No Comments

SOURCE: Enterprise Apps Today

The basic aim of data virtualization, whose first solutions arrived around 2001, is to allow users to query across differing data sources in real time. That means that any DV solution needs three brand spanking new (in 2001) technologies:

1.       A way to gather data from any data stores accessed by different vendors’ databases or file systems or applications in real time;

2.       A global metadata repository that shows not only what data was out there, anywhere, but also the relationships between the data in various data stores;

 

3.       A common format across any and all data types that allows DV when it combines the data to present to the end user the relationships between the data, not just differing formats side by side.

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DATA and ANALYTICS 

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