Now a combination of the cloud and machine learning is enabling businesses to wrestle that data into intelligible answers to big questions.
Machine learning, which came out of the study of pattern recognition and computational learning, is perfect for this. The technology uses algorithms that learn from the repeated use of data, enabling them to become better and better at finding insights and answers without being expressly programmed on where to look for them.
The more data machine learning has to work with, the better it learns.
With bigger stores of data, machine learning can do a better job of answering questions for businesses. The technology could help an oil company find information for finding the next great oil pocket, a grocery story chain on how to sell more butter, or for an automaker to build a safer, more energy-efficient automobile.
"Companies are digital pack rats because it doesn't pay to throw data away," said Greg DeMichillie, director of product management for Google's cloud platform. "Now it's how to make sense of this needle in a hay stack … What we see is people don't want to take their server from on-premise to a cloud and leave it as is. We've only begun to scratch the service on how machine learning can make it better. It helps you answer the questions you didn't even know before to ask."
Machine learning, according to DeMichillie, is bringing on the next transformative wave in IT and the cloud.
"It's the only way to make sense of the data that we have," he said. "At the scale we're talking about, it's just not possible without the cloud. Most companies would never have the ability to build out a machine-learning infrastructure. It's not economical for an on-premise environment."
Jorel Perez, a San Antonio-based mobile web developer who works for a Fortune 500 financial services company, said he sees companies increasingly focusing on what they can do with all the information they have in the cloud.
"We're starting to realize how much data we actually have, Perez said. "hey're like, 'Wow! We actually have a lot of data.' We're tracking a lot of things. Now they're like, 'What do we do with it?' What can we do beyond initial queries?"
Dinesh Ganesan, a consultant with Octo Consulting Group, which works with government agencies, said many enterprises are looking to Google for help with their cloud analytics.
"[Amazon Web Services] has data analytics tools, but there's a perception that Google has much more muscle there," Ganesan said. "This is Google's strength – analytics and deep learning. Everybody knows deep learning is very cool. Sure. But what is your use case with it? Google needs to step in there and show them that it's not just cool but can do things for them."
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