Alternate framework for distributed computing tames Big Data’s ever growing costs

The sheer volume of ‘Big Data’ produced today by various sectors is beginning to overwhelm even the extremely efficient computational techniques developed to sift through all that information. But a new computational framework based on random sampling looks set to finally tame Big Data’s ever-growing communication, memory and energy costs into something more manageable.