Google Opens Up 'BigQuery' Data Crunching Servers To Small Business Owners
Google has offered businesses the chance to use its data servers to crunch huge amounts of data for a fraction of the usual cost.
Using its BigQuery service Google will let businesses process billions of rows of data in seconds, initially free of charge.
A preview version the system was unveiled at Google I/O in 2010, but was only used by a small number of developers and developers.
Now the company aims to allow many more companies to access its powerful system.
The move, which is a challenge to establishing analytics companies including Oracle, IBM, SAS, SAP and Microsoft, could rock an industry which is set to grow more than 6.8& between 2010 and 2014 according to companiesandmarkets.com.
In a post on a company blog, Google said that many businesses could would find uses for data crunching.
"Imagine a large online retailer that wants to provide better product recommendations by analysing website usage and purchase patterns from millions of website visits," wrote Google product manager Ju-Kay Kwek.
"Or consider a car manufacturer that wants to maximize its advertising impact by learning how its last global campaign performed across billions of multimedia impressions. Fortune 500 companies struggle to unlock the potential of data, so it's no surprise that it's been even harder for smaller businesses."
Google also announced a new user interface for the service, and said the results of users' data searches would be viewable via its cloud storage solution.
Michael J. Franklin, who is a professor of computer science at UC Berkeley, said BigQuery allowed a scale of data processing "that is simply jaw-dropping given the current state of the art."
The service is currently available free of charge, though Google plans to charge for the service at a later date.
Others have commented, however, that making useful analysis of the data crunched by systems like BigQuery is complex, and that it is unlikely that most small businesses will find an immediate use for it.
"Generating analytical results of high significance for business decisions has not been easy historically," Christian Lagerling from GP Bullhound, told the BBC.
"It typically requires significant PhD level engineering hours to be able to fully comprehend and apply the results."