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System z Helps Address the Data Analytics Power Crunch


The global populace daily creates 2.5 quintillion bytes of data, according to IBM, and 90 percent of the world’s data was created in the past two years. With the world giving birth to so much data so fast, the technologies data centers are adding to process it all are likewise making increasingly enormous power demands.

In response, IBM is positioning System z technology as well as InfoSphere BigInsights and InfoSphere Streams software, as solutions to the power and processing needs of expanding volumes of data.

Power Crunch

The current data explosion, which presents more challenges than size alone, bears defining. It’s largely unstructured data that has grown in size, speed, variety and complexity—so much, so fast, that data centers cannot store or process it all by traditional means.

And, the untraditional means that data centers are applying—the swiftly multiplying high-density hardware racks, the added network and power infrastructure, the new and often experimental technologies and software, and the added services—are devouring an advancing share of the world’s available energy. “Some data centers are using 40kW-per-rack or more,” says Nick Razey, CEO of NGD Europe (London), Europe’s largest tier three data center.

Already, the compute cycles and industry energy mandates that predate the data explosion are already draining the raw power supply to the data center. “Before long, there will be a power crunch, exacerbated by these large amounts of data,” says Razey.

“The available power supply in the UK grows by 0.7 percent per year,” he explains, “but the overall size of data here is doubling every 18 months.” Data centers have traditionally used 2 to 3 percent of the available power, Razey continues, but if these facilities greatly increase their power draw in an attempt to sate the appetite for data, a serious power shortage will result.

Billions of netizens, sensing devices and other data-generating machines ensure the data glut isn’t going away. Data centers, therefore, must find a way to process the data behemoth while curtailing its energy cravings.

David Geer (www.linkedin.com/in/daviddgeer ) is a freelance technology journalist.


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