In the World of Big Data Analytics, Azure Is More Than Just a Pretty Color

In the latest issue of Statistica Monthly News (yes, you can subscribe for free), our readers found a link to a webcast that talks all about Statistica’s new partnership with Microsoft, a relationship that produces some incredible hybrid cloud functionality for data analysis using Azure Machine Learning (ML).

We are talking about a hybrid cloud solution whose powerful functionality completely belies Azure’s namesake: a shade of bright blue often likened to that of a cloudless sky. Cloudless? Hardly. The Statistica-Microsoft partnership is all about the Cloud!

The fun story in the webcast describes how one website was running an analytics program as an API on Azure. Designed to guess ages and genders of people in photographic images, the site was expecting a few thousand submissions, but it went from zero to 1.2 million hourly visitors within just two days of going live, and up to seven million images per hour. By day six, 50.5 million users had submitted over 380 million photos! Normally, we would hear about sites crashing with such a viral overload. But this site kept humming along even when the action ramped up so dramatically, primarily because Azure scaled dynamically as intended, handling the unforeseen load like a champ.

Think about embedding this kind of cloud access and flexible scalability as a directly callable function inside Statistica—well, that just makes way too much sense, right? But that is what’s happened! Azure ML is really a development environment for creating APIs on Azure, with the intent to enable users to have machine learning in any application, whether that is a web app or a complex workflow driven by Statistica. For instance, you can host your complicated models in the cloud with Azure and run non-sensitive, big data analytics out there—a very practical time saver and money saver. Then you can bring those analyzed results back down to join perhaps more sensitive data and analytics output behind your firewall. You can learn more when you watch our “Cloud Analytics” webcast.