In an earlier post, Mike Cornell of BlueGranite introduced Azure ML – Microsoft’s Machine Learning engine in the cloud. Mike showed you how you can build an experiment, then publish it for use in your self-service BI application. In this video, we’ll go one step deeper and show you how to connect your data stored in HDInsight.
Why combine HDInsight with Azure ML?
HDInsight provides the ability to work with massive amounts of data – billions of data points – using the power of distributed processing. HDInsight provides functionality to pre-process and shape that massive amount of data into a form that can be easily consumed by Azure ML.
In addition, it provides a way to add structure to un-structured and semi-structured data allowing analysts working in Azure ML to quickly put together models and experiments. These models and experiments on unstructured data can provide insights to customer buying patterns, buyer sentiment, and forecasting predictions at a pace never before possible.
With the ability to connect directly to HDInsight from the Azure ML workspace, gaining insights from data has never been closer at hand.
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