has been on quite a cloud roll lately and today it announced called , which enables companies to use the power of the cloud to build applications and APIs based on big data and predict future events instead of looking backwards at what happened.
The product is built on the machine learning capabilities already available in several Microsoft products including Xbox and Bing and using predefined templates and workflows has been built to help companies launch predictive applications much more quickly than traditional development methods, even allowing customers to publish APIs and web services on top of the Azure ML platform.
, corporate vice president at Microsoft, who was in charge of the Azure ML, and spent years at Amazon before joining Microsoft to lead this effort, said the platform enables customers and partners to build big data applications to predict, forecast and change future outcomes.
He says this ability to look forward instead of back is what really stands out in this product.
“Traditional data analysis let you predict the future. Machine learning lets you change the future,” Sirosh explained. He says by allowing you to detect patterns, you can forecast demand, predict disease outbreaks, anticipate when elevators need maintenance before they break and even predict and prevent crime, as just a few examples.
Sirosh says the cloud really changes the dynamic here because it provides the ability to scale, and the service takes care of much of the heavy lifting that would have taken weeks or months for companies trying to do it themselves in-house in a data center.
“The cloud solves the last mile problem, Sirosh explained. Before a service like this, you needed data scientists to identify the data set, then have IT build an application to support that. This last part often took weeks or months to code and engineer at scale. He says Azure ML takes that process and provides a way to build that same application in hours.
What’s more is it supports more than 300 packages from the popular used by many data scientists.
Sirosh says the hope is that as more people use the platform and generate APIs and applications, and create what he called, “a virtuous cycle between data and APIs. ” People have data. They bring it to [Azure ML] to create APIs. People hook into applications then feed data back to the cloud and fuel more APIs, “he explained.
The product is currently in confidential preview, but Microsoft did mention a couple of examples including Max 451, a Microsoft partner working with large retailers to help predict which products customers are most likely to purchase, allowing them to stock their stores before the demand.
Carnegie Mellon University is working with Azure ML to help reduce energy costs in campus buildings by predicting and mitigating activities to reduce overall energy usage and cost.
Microsoft is not alone in this space, however. last winter for similar types of machine learning application building and just last week a startup called .
Azure ML goes into public preview next month. There is no word yet on the official launch date.