Microsoft Azure Analytics is Microsoft’s Analytics stack in the cloud. Within Azure you will find various solutions that help you to make data transparent. This can be traditional BI, but also complex predictive models. Such as a self-learning system that recognizes patterns. When you look at your business processes with Azure Machine Learning, for example, you can see that the system indicates lines that you have never seen before. By looking at the past, it is easier to extend the line. With this as a basis, a lot of applications become available.
Companies of the future know what is going on inside their premises, but also far beyond. They know what is happening now, but also what will happen next month. But how do you get this wisdom? The answer is to be found within existing data that tooling from the Azure Analytics stack reveals. Questions you can answer are, for example, ‘when do we need to schedule time to provide machine 9 service’ (Predictive Maintenance). Or ‘which article is going to sell well next week in the city of London?
There is a some level of certainty. You can never be 100% sure that the predicted result will come true. It’s not a crystal ball. But whether or not you can prepare for a peak in sales is where you can make a difference. The difference between winning over a competitor or lagging behind.