Azure ML: Will Machine Learning Change Everything?
One of the most revolutionary technologies emerging out of Microsoft’s R&D in the past 12 months is Azure ML, a product so advanced that almost no one knows that it exists, let alone what it does. ML stands for Machine Learning and Azure ML is a set of modeling and development tools intended to provide this type of artificial intelligence to today’s companies. My feeling is that Azure ML is a game changer that has the potential to take all of our businesses to much higher levels of productivity. The question is, does the average business have the ability to take advantage of this power? Through a series of blogs we will attempt to answer that question.
The heart of Azure ML is “Predictive Analytics” the ability to use data—usually lots of it—to make objective predictions and/or decisions. You can look at it as the next phase of Business Intelligence.
Business Intelligence (BI) is loosely defined as organizing data in a meaningful way so that humans can understand their company’s past and current status or health or progress more thoroughly. The more advanced BI applications these days allow you to view highly informative “dashboards” based on many different parameters (for example dates, regions, salespeople, product types), and to change these parameters in order to learn a great deal about your business.
Predictive Analytics, on the other hand, is about having the computer create insights automatically from that data. As an example, BI would let you view how certain products have sold to certain types of customer segments through dashboards that you can manipulate. Yet Predictive Analytics might be able to tell you what types of products to buy during certain seasons based on its own historical analysis of those sales patterns.
So we have a disruptive technology that can utilize our data to help us to make business decisions based on objective criteria, not leaving us to rely upon our own subjective experiences. This truly can change everything about the way we run our businesses. The question is how we can utilize this technology. In our next blog we will look at real examples of Machine Learning in action.