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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...

Large Scale Analytics in the Enterprise

August 9, 2012 No Comments

SOURCE: Think Big Analytics

The growth of Internet businesses led to a whole new scale of data processing
challenges. Companies like Google, Facebook, Yahoo, Twitter, and Quantcast now
routinely collect and process hundreds to thousands of terabytes of data on a daily basis.
This represents a significant change in the volume of data which can be processed, a
major reduction in processing time required, and of the cost required to store data. The
most important of the techniques used at these companies is storing data in a cluster of
servers and using a distributed data processing technique Google invented, called
MapReduce. Facebook, Yahoo, Twitter, and Quantcast all process data with an open
source technology implementation of MapReduce called Hadoop.

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