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<strong>6 Tips For Training Your Employees About Cybersecurity</strong>

6 Tips For Training Your Employees About Cybersecurity

This discussion will focus on establishing an all-encompassing information...

How Square Improves Shareholder Engagement and Enhances Overall IR Efforts with Actionable Insights 

How Square Improves Shareholder Engagement and Enhances Overall IR Efforts with Actionable Insights 

The healthcare industry is in no way exempt from...

Solving the steam_api.dll Missing Issue

Solving the steam_api.dll Missing Issue

Usually this error is faced by the gamers -...

How Security in Tech is Being Reinforced

How Security in Tech is Being Reinforced

In an increasingly digital world, security has become a...

2022 Business Spend Management Benchmark Report

2022 Business Spend Management Benchmark Report

Read the 2022 Coupa Benchmark Report to explore 20...

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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