Earlier this year I wrote a post that showed how to perform sentiment analysis in Dynamics CRM using Microsoft Azure Text Analytics. Azure Text Analytics makes it incredibly easy to use sentiment analysis (with English text only), but the full Azure Machine Learning offering is much more powerful. In today's post I will show how to create a custom predictive web service in Azure ML and make predictions with it in Dynamics CRM. One of the exciting announcements about Dynamics CRM 2016 is that it includes some sort of integration with Azure ML, so what's the point of this blog post? For this demonstration I am using data from the AdventureWorks data warehouse sample database to build a model to predict whether a contact in CRM is likely to be a bicycle buyer.
Artificial Intelligence (AI) has emerged as one of the most disruptive forces behind the digital transformation of business. Our mission is to bring AI to every developer and every organization on the planet, and help businesses augment human ingenuity in unique and differentiated ways. Developers and data scientists are at the heart of driving this innovation force and we are committed to providing them the best tools to make them successful.
It was just two years ago that Microsoft and VMware were at odds over Microsoft making a preview of VMware virtualization on Azure. When that preview was announced, VMware officials noted Microsoft's preview was developed without VMware's participation and was neither certified nor supported by VMware. What a difference a couple years make. On April 29, Microsoft and Dell Technologies (a majority shareholder in VMware) announced via an "expanded partnership" that the two would provide customers with "a native, supported, and certified VMware experience on Microsoft Azure." The newly announced Azure VMware Solutions provides a common operating framework for running, managing and securing applications across VMware and Azure.
Cloud platforms like Azure provide the best options for organizations in their digital transformation. Innovation Labs on Cloud In today's context, organizations adopt a build versus buy approach based on their core competencies and innovation needs. When the business functionality is non-core to their operation like a HR operations, organizations tend to go with SaaS based solutions. However when there is a need to make the organization stand apart in the competition, then the core functionality needs to be built. When it comes to the building new applications and services on cloud, the traditional infrastructure as a service helps a lot, but the flexibility and the extensibility of PaaS (Platform as a Service) helps to a great extent in reducing the time-to-market.