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Microsoft Azure Machine Learning, the company’s cloud-based predictive analytics offering, is now generally available, the company announced during this week’s Strata + Hadoop World big data conference in San Jose, Calif. The solution joins another high-profile Microsoft release during the event, the first public preview of Azure HDInsight on Linux.
With roots in the company’s advanced research department, the service is aimed at helping enterprises quickly deploy predictive analytics solutions based on their data. With data scientists in short supply—and commanding sky-high salaries—Microsoft is banking on businesses flocking to its cloud for their big data analytics needs.
“In mere hours, developers and data scientists can build and deploy apps to improve customer experiences, predict and prevent system failures, enhance operational efficiencies, uncover new technical insights, or a universe of other benefits,” stated Microsoft’s T. K. Rengarajan, corporate vice president of the Data Platform unit, and Joseph Sirosh, corporate vice president of Machine Learning, in a joint Feb. 18 announcement. “Such advanced analytics normally take weeks or months and require extensive investment in people, hardware and software to manage big data.”
Organizations lacking in big data expertise can plug the gaps using the Machine Learning Marketplace. It provides developers with “APIs [application programming interfaces] and finished services, such as recommendations, anomaly detection and forecasting, in order to deploy solutions quickly,” they said.
Currently, customers can find APIs for social media sentiment analysis, customer churn prediction and anomaly detection, among several others. And in a nod to the company’s newfound fondness for the open-source community, they described the Python programming language as “a first class citizen in Azure Machine Learning Studio, along with R, the popular language of statisticians.”
In a separate blog post detailing the announcement, Sirosh revealed that data integration specialist Informatica has come onboard as a partner. “The Informatica Cloud service allows customers to pull data from a variety of on-premises systems and the cloud—including from SaaS applications such as Salesforce.com, Workday, Marketo and more—into Azure Blob storage,” he said.
Basing Web services on Azure Machine Learning has been “completely revamped,” said Sirosh. “It is now far more intuitive to take a data science workflow and create an analytics web service from it—it takes only minutes.” Microsoft is also tossing in an Excel client, allowing customers to test their new Web services against their own data.
A new, social-enabled gallery of Azure Machine Learning experiments encourages users to share their discoveries and delve into the process of building data models. “You can ask questions or post comments about experiments in the gallery or publish your own. You can share links to interesting experiments via social channels such as LinkedIn and Twitter,” said Sirosh.
Despite spending a half-year in preview, Azure Machine Learning has already attracted some large customers, according to Microsoft. Early adopters include Pier 1, Carnegie Mellon and eSmart Systems.