Azure helps unlock our DNA and find 2 new prehistoric ancestors

These Denisovan discoveries were based on statistical models created by Cox and his colleagues and run on Microsoft Azure, which proved a key factor in their project’s success. Massey, unlike many other universities, does not have its own on-premises computer facility to carry out big data-based research.

“These are big, costly computers, but their capacity is limited. Lots of people want to use them, and that means that it is very hard to get the compute time you need when you need it. You have to wait in line,” Cox explains.

In this case, the team went with a Microsoft cloud option. “Azure works well for us. It has scalability and flexibility. It gives us the freedom to work at the pace that we need to get answers.”

Science moves fast

Cox estimates that if the team had instead used an in-house IT facility, their work might have taken an extra six months, year, or more to complete.

“It’s hard to say. But actually, it might have been never. That’s because the amount of computing time we needed would have meant that someone else probably would have got to the answers before we did, and they would have published before us. Science moves fast, and the questions would have been addressed by others if we hadn’t got there at the speed we needed.”

Businesses and bureaucracies routinely use the power of the cloud to sift through, analyze, and harness mountains of big data in fast, secure, and flexible ways. Cox says cloud computing brings the same benefits to the laboratory. “Processing so much data can be boring and laborious,” he says. “Azure frees us to do other things to develop our research.”

New technologies and solutions that operate in the cloud and leverage artificial intelligence and machine learning promise to accelerate the pace of research. And the ability to process lots of data quickly can also open up new directions for scientific inquiry as it did for Cox and his colleagues.